Smartphone-Based Apparatus and Method

ABSTRACT

A method for obtaining a point-of-collection, selected quantitative indicia of an analyte on a test strip using a smartphone involves imaging a test strip on which a colorimetric reaction of a target sample has occurred due to test strip illumination by the smartphone. The smartphone includes a smartphone app and a smartphone accessory that provides an external environment-independent/internal light-free, imaging environment independent of the smartphone platform being used. The result can then be presented quantitatively or turned into a more consumer-friendly measurement (positive, negative, above average, etc.), displayed to the user, stored for later use, and communicated to a location where practitioners can provide additional review. Additionally, social media integration can allow for device results to be broadcast to specific audiences, to compare healthy living with others, to compete in health based games, create mappings, and other applications.

The cost and accessibility of traditional medical diagnostic instrumentscan and needs to be improved. Currently, diagnosis of disease can takedays to weeks while results are sent off to a laboratory, and manydiseases still cannot accurately be detected. Devices capable of quicklyand accurately diagnosing multiple conditions could be applied tosituations ranging from nutrition and vitamin management in first-worldlocales to antibiotic and vaccine triage in third-world villages. Ifcreated and packaged correctly, such devices could ease the burden ongateway physicians, provide impoverished countries with now inaccessiblediagnostic capabilities, protect combatants from biological warfareagents, and increase health care access to the average person.

Lateral flow immunochromatographic assays have been widely adopted fordiagnosing various diseases and medical conditions in point-of-caresettings. These tests are rapid, simple and produce colorimetric signalsthat can be interpreted by untrained personnel. Unfortunately in mostcases, the data interpretation of lateral flow tests depends on the endusers who have to make judgments based on their observations, andtherefore the results are largely susceptible to error. In recent years,there has been a desire to enhance the accuracy of the measurements,and/or to obtain quantitative information from the lateral flow tests.One exemplary case where higher accuracy is essential, and thesubjectivity in determining the test outcome is inappropriate, is forthe testing of controlled substances using the lateral flow tests.

The high demand for quantitative readouts has been reflected well by theincreasing number of semi-portable readers on the market for analyzingthe lateral flow assays. However the cost and size of these specializedreader systems still remain to be significant, and hamper theirwidespread adoption for many end consumers. Also, most of the commercialreaders for lateral flow tests are only semi-portable and/or requireconnection to the computer systems to perform the required analysis. Forexample, the sizes of ESEQuant Lateral Flow Immunoassay Reader (Qiagen,Germany) and SkanMulti (Skannex, Norway) are still relatively bulky andthus are not truly portable. Furthermore, SkanMulti functions only as animaging system and requires a computer to analyze the acquired data.

One implementation of state-of-the-art diagnostics is as smartphoneand/or tablet (i.e., portable computing) accessories where thecomputational power, read-out, data storage, and connectivity areprovided by an existing device. The smartphone has penetrated nearly allaspects of our lives, affecting how we consume media including news andentertainment, how we track our finances and pay for goods and services,and how we monitor our health and fitness. However, for all of thebenefits smartphones have provided, there is still little or no directconnection between smartphones and in vivo biochemistry. By enabling adirect link between a smartphone and small molecule detection,monitoring, and tracking, a number of new benefits could be realized inthe fields of medicine and healthy living, including, e.g., simplediagnosis of disease and nutrient deficiencies; monitoring and trackingof existing conditions; and social media-enabled healthy living updates,competition, game playing, and mapping.

Moreover, some companies have indeed explored smartphone solutions forreading the lateral flow tests. For example, mReader software(MobileAssay, Colorado, USA) can be installed on smartphone systems andused to analyze the test strip images taken from the smartphone cameras.Although the use of smartphone systems to replace the specializedreaders effectively addresses the aforementioned limitations, they do soat the expense of reliable imaging as the images are taken in the openenvironment whose lighting conditions cannot be accurately controlled.

Suboptimal nutrition is one of the most acute problems facing thedeveloped and developing world today. Worldwide, there are moredisability-adjusted life years lost to malnutrition than any othermedical condition; it is reported that over 1,000,000 people die everyyear from vitamin A and zinc deficiencies, and 30% of all cancers arerelated to poor diet (by comparison genetics and obesity account foronly 5% and 10% of all cancers respectively). Optimal pre-natal maternalfolic acid levels are well co-related with a reduction in neural tubedefects and evidence suggests that fetal brain development is enhancedby docosahexaenoic acid (DHA) intake. Micronutrient (i.e., vitamins andminerals) deficiencies have been tied to dozens of different healthconditions including anemia, rickets, scurvy, cardiovascular disease,and cancer. Additionally, recent work has linked vitamin deficiencies toobesity, one of the major challenges facing the current generation.

The Copenhagen Consensus has identified tackling vitamin andmicronutrient deficiencies as the most cost-effective intervention tofurther global development and progress in published reports since 2004.Domestically, the Institute of Medicine has concluded half of olderadults in the United States who had hip fractures had serum levels of25(OH)D less than 12 ng/mL; (25-hydroxyvitamin D [25(OH)D] is consideredto be the best indicator of vitamin D; and, that levels below 20 ng/mLare inadequate for bone and overall health. The vast majority of vitaminand micronutrient analysis is done through blood collection viavenipuncture, which is then sent away to a centralized laboratory. Thisanalysis is slow, expensive, requires trained personnel, and is notwidely available, particularly in resource-limited settings wheremicronutrient deficiency is most harmful. A combined HPLC-MS method isconsidered the industry standard for vitamin D testing, however ELISAkits and similar immunoassays are comparable in terms of sensitivity andaccuracy, while being better suited for adaption to home use. Sincemicronutrient deficiencies are not often clinically obvious, these testsare typically done at the insistence of the patient. The fact that somany Americans are vitamin deficient testifies to the fact that thecurrent methodologies are not working.

Salivary cortisol is a routinely used biomarker of stress and relatedpsychological diseases. Commonly, cortisol is elevated in patients whoexperience a sudden stressor and returns to normal after a period oftime whose length is dependent on the strength of the stressor. Inpatients with chronic stress disorders, such as PTSD, it has beendifficult to co-relate absolute levels of cortisol at any given timewith the diagnosis of a disorder due to the large number of confounders.A better approach would be to track cortisol, and other biomarkers, overtime to look for trends that could be indicative of the onsetpsychological disease.

Every year hundreds of millions of people suffer from infectiousdiseases including respiratory infections, HIV/AIDS, diarrheal diseases,tuberculosis, and malaria. The agents that cause these diseases,including bacteria, viruses, fungi, etc., are often easily manageablewith proper identification yet routinely go undetected because of thecosts and difficulties associated with diagnostic technology. In somecases, such as tuberculosis, identifying the disease rapidly and onlocation can allow for preventative measures prohibiting the diseasefrom spreading further. In other cases, such as HIV, keeping anacute-eye on antibody levels is critical in tracking the progress of thedisease.

Kaposi's sarcoma (KS) is an opportunistic infectious cancer that firstbecame widely known during the acquired immunodeficiency syndrome (AIDS)epidemic of the 1980s. During this time period, the appearance ofsymptoms of KS, red lesions on the skin, became signs that an individualwas infected with human immunodeficiency virus (HIV) and KS itselfbecame known as an AIDS-defining illness. As the battle against AIDSwaged on, the introduction of highly active anti-retroviral therapy(HAART) helped reduce KS incidence. Years later, however, HIV infectedindividuals still contract KS at a higher occurrence than when comparedto the pre-AIDS era. Today, KS is the fourth leading cancer insub-Saharan Africa, and in some countries, such as Uganda, is the mostprevalent cancer in men. The root cause of KS is Human herpes virus 8(HHV-8), more commonly referred to as Kaposi's sarcoma associated herpesvirus (KSHV). While the virus is often asymptomatic in healthyindividuals, a number of populations, including those immune-compromisedby HIV, are vulnerable to its symptoms. The virus is commonly believedto be transmitted through saliva and in some regions rapidly spreads,beginning in childhood affecting large portions of the population,reaching seroprevalence of over 50%. Like other herpes viruses, KSHV canestablish a latent infection and remains without causing any disease forthe remaining life in most infected hosts, being necessary but notsufficient of KS development.

In the developed world, medical professionals diagnose KS withsufficient accuracy. If typical hematoxylin and eosin (H&E) staining areapplied to a KS biopsy section a number of unique features can beobserved, including many and large vascular spaces as well as highnumbers of spindle cells thought to be of lymphatic endothelial origin.However, due to the existence of similarly presenting diseases, such asbacillary angiomatosis (BA), identification of these features is notsufficient for diagnosis of KS. In modern hospitals this is solvedthrough immunohistochemistry staining for protein markers of KSHV, orthrough application of PCR for KSHV sequences. However, neither of thesetechniques is readily adaptable for use in the developing world where KSis most prevalent.

The alarming increase in premature deaths due to heart disease in thedeveloped world has resulted in numerous efforts to make bloodcholesterol measurements accessible outside the clinical setting. It isestimated that 60% of adults in the US have high cholesterol (over 200mg/dl), with 37 million among them having very high cholesterol (over250 mg/dl). Long-term studies on the effect of serum cholesterol oncoronary heart disease mortality indicate that there is a 17% increasein mortality rate for every 20 mg/dl increase in serum cholesterollevels above 210 mg/dl. Monitoring cholesterol levels is importantbecause it can empower people to make lifestyle choices for preventingheart disease later in life. For some people, improving diet andincreasing exercise can lower overall cholesterol, but in some casesmedication needs to be prescribed. Products such as Cardiochek andCholestech have been on the market for over a decade; however homecholesterol testing is still not common. A recent study suggested thatcurrent cholesterol kit users are interested in easier ways of trackingresults and that they would test more frequently if supplies were moreaffordable. The accuracy of those devices is also a major user concernand has been addressed in several publications.

Finding a solution to the aforementioned challenges and problemsdirectly motivated the development of lab-on-a-chip based point-of-carediagnostics beginning some 15 years ago. The technical vision behindthese kinds of systems comprised two parts: a consumable “chip” thatcontained microfluidics and a biosensor, and a “reader” instrument thatinterpreted the signal from the chip and provided results to theoperator. Since this vision was first put forward, the technology hasadvanced at an incredible rate to the point where we now have devicesthat can operate over a million microfluidic valves in parallel,portable PCR machines for pathogen detection, nanosensors that candetect a handful of molecules, and numerous other systems. Thesedevelopments have significantly reduced the size of the sample requiredto perform a blood analysis.

Smartphones have the potential of addressing all these issues byeliminating the need for separate test kits. Test strips could be imageddirectly on a smartphone and the processed data can be stored fortracking or sent via e-mail directly to a physician. Smartphoneaccessories for the detection of biomarkers in bodily fluids have beenthe subject of extensive investigation because they have the potentialof greatly decreasing the cost and increasing the availability of heathcare in the world.

It is predicted that by 2016 there will be 250 million smartphones inuse in the US. A good portion of the complexity required to make andinterpret a quantitative in-vitro measurement is already embedded insmartphones, resulting in a paradigm shift in the “razor and blades”model. Put simply, most consumers now already own the expensive part,the “Razor,” in the form of a smartphone; all one needs then is theblades.

The inventors have recognized that quantitative analyses of bodilyfluids like sweat, saliva, urine, blood, and others would provide a deepwealth of physiological information. The inventors have also recognizedthat, in addition to mobile, point-of-collection devices and methodsthat address the challenges outlined above, there is an intense need forthe ability to obtain accurate, consistent, and standardizedquantitative measurements and, independent of the smartphone platformbeing used, the benefits and advantages of which would contribute tobetter quality of life.

These and other objects, benefits, and advantages provided by thesolutions enabled by the embodied invention will be described in detailbelow with reference to the accompanying figures and as set forth in theappended claims.

SUMMARY

Embodiments of the invention are methods and systems (and componentsthereof) for obtaining and presenting (i.e., displaying or communicatingout) quantitative, colorimetric-based measurements of target analytes aswell as enabling accurate reading and analyses of lateral flow assaysusing a smartphone platform that is accurate, consistent and reliableindependent of the smartphone platform being used.

DEFINITIONS

As used herein, the term ‘smartphone,’ ‘smartphone platform,’ or‘smartphone-type device/system’ (hereinafter “smartphone”) means amobile apparatus that is capable of running a programmed applicationsuitable for executing the embodied functionality. While suitabletraditional smartphones may include products such as, e.g., the iPhone,iPad (Apple, Inc.), Android-based devices, and other well known devicesand associated operating systems, the term smartphone as discussed andembodied herein is intended to include any digital mobile device such assmartphones, tablets, phablets, smart watches, and other current orfuture ‘smartphone’ platforms having similar minimal functionality. Inthis regard and for the sake of clarity, a ‘laptop’ computer would notnecessarily be covered under the definitional use of the term‘smartphone;’ nor would a computing device that could be made ‘portable’or ‘mobile’ by an accompanying apparatus that might give it portabilityor mobility. Thus, the term ‘smartphone’ will be used herein (includingthe claims) to mean devices as discussed within the paragraph above.

The term ‘modular test platform’ as may be used herein (and in theclaims) means a reusable or disposable medium capable of receiving atarget sample and having the appropriate chemistry and form factor to beused in the embodied smartphone and enable the embodied colorimetricreaction. Practical examples of embodied modular test platforms include,but are not limited to, various custom or commercially available ‘teststrips.’

The term ‘rear surface’ as may be used herein (and in the claims) inconjunction with ‘test strip’ means the surface of the test strip facingaway from the smartphone camera in an operational mode of the system.

The term ‘colorimetric test,’ ‘colorimetric assay,’ or ‘colorimetricreactive test platform’ as may be used herein (and in the claims) meansat least a measurable color change from one color to a different coloror a measurable change in intensity of a particular color, in thepresence of the analyte.

The term ‘rapid’ as may be used herein (and in the claims) means‘essentially in real time’ (e.g., seconds, minutes).

The term ‘point-of-collection’ as may be used herein (and in the claims)means making a rapid target measurement at the time a sample iscollected on a modular diagnostic test platform (e.g., test strip) inpossession of the user and then inserted into the embodied smartphonesystem, not at a later time, for example, after a sample has beencollected and sent to a laboratory.

The term ‘suitable’ as may be used herein (and in the claims) meanshaving the qualities that are correct, needed, or appropriate forsomething, especially as a person skilled in the art would understand.

The term ‘about’ as may be used herein (and in the claims) means theamount of the specified quantity plus/minus a fractional amount thereofthat a person skilled in the art would recognize as typical andreasonable for that particular quantity or measurement.

The term ‘substantially’ as may be used herein (and in the claims) meansas close to or similar to the specified term being modified as a personskilled in the art would recognize as typical and reasonable; for e.g.,within typical manufacturing and/or assembly tolerances, as opposed tobeing intentionally different by design and implementation.

An embodiment of the invention is a method for obtaining apoint-of-collection, selected quantitative indicia of an analyte on atest platform with a smartphone. Illustrative method steps includeproviding a modular, colorimetric reactive test platform having a testregion and a calibration region; providing an analyte to be tested onthe test region of the modular, colorimetric test platform, wherein thetest region is adapted to enable a colorimetric reaction to the analyte;obtaining a color image of the test region containing the analyte andthe calibration region; selecting an array of pixels in each of thecolor images of the test region containing the analyte and thecalibration region; determining a median RGBA color value for each ofthe arrays of pixels; converting the median RGBA color value for each ofthe arrays of pixels to a respective Hue-Saturation-Luminosity (HSL orHSV) test color space value and a HSL or HSV calibration color spacevalue; providing a calibration indicia that relates a selectedquantitative indicia of the analyte to a characteristic of the HSL orHSV calibration color space value; and associating a median HSL or HSVtest color space value with the HSL or HSV calibration color space valueto determine the selected quantitative indicia of the analyte. Theembodied method may further be characterized by the followingillustrative, exemplary, non-limiting aspects, features, or steps:

-   -   wherein the colorimetric reactive test platform is sensitive to        at least one of a chemical colorimetric reaction, an enzymatic        colorimetric reaction, and a gold nanoparticle colorimetric        reaction;    -   wherein the modular, colorimetric test platform is a disposable        test strip;    -   wherein the indicia of the analyte is one of pH, cholesterol,        and vitamin D;    -   wherein the calibration region maintains a constant color in the        presence of a varying amount of the selected indicia of the        analyte;        -   wherein the calibration region includes a plurality of            calibration regions each of which has a different            calibration color;    -   wherein the calibration indicia is a calibration curve that        relates the selected quantitative indicia of the analyte to a        hue value of the HSL or HSV calibration color space value;    -   obtaining the color image of the test region containing the        analyte and the calibration region using a smartphone including        a light source and an image detector;        -   displaying the determined selected quantitative indicia of            the analyte on the smartphone;        -   providing a smartphone accessory that can be removeably            coupled to the smartphone, wherein the smartphone accessory            is adapted to receive the modular, colorimetric test            platform, further wherein at least one of the modular,            colorimetric test platform and the smartphone accessory            includes a light diffuser and/or a light-diffusing pathway            so as to ensure a uniform and repeatable illumination of at            least a desired region of the modular, colorimetric test            platform, further wherein the smartphone accessory is            substantially light-tight when the test platform is disposed            therein, so as to enable consistent internal illumination            conditions independently of any external conditions;            -   wherein obtaining a color image of the test region                containing the analyte and the calibration region                further comprises illuminating a rear surface of the                test strip that is facing the light source with diffused                light from the light source            -   wherein the light source is one of an internal                smartphone flash source and an external LED source;        -   time stamping the determined selected quantitative indicia            of the analyte and storing the determined value for future            access;        -   location stamping the determined selected quantitative            indicia of the analyte and storing the determined value for            future access;            -   storing the time and/or location data in at least one of                a readable file in the smartphone, an external readable                file, and in a Cloud file;            -   determining a temporal and/or a location trend of a                plurality of the determined selected quantitative                indicia of the analyte;        -   correlating the determined selected quantitative indicia of            the analyte to a related selected metric and displaying a            value of the related selected metric on the smartphone;    -   wherein the analyte is one of sweat, saliva, blood, tears,        urine, and other bodily fluids;    -   wherein the step of obtaining a color image of the test region        containing the analyte and the calibration region comprises        illuminating a rear surface of the modular, colorimetric test        platform.

An embodiment of the invention is a method for obtaining apoint-of-collection, selected qualitative and/or quantitative indicia ofan analyte on a test platform. In an exemplary aspect, the methodinvolves providing a modular assay test platform (e.g., test strip)having at least one test region and a control region; providing ananalyte to be tested on the at least one test region; obtaining an imageof the at least one test region containing the analyte and the controlregion;

selecting an array of pixels in the image of the at least one testregion containing the analyte and the control region; determining a RGBAcolor value for each of the arrays of pixels; extracting a test imageregion for analysis; converting the RGBA array to an alternate colorspace as determined by the specific test including but not limited toHSL, HSV, or greyscale; determining one of a median, mean, maximum,minimum, or other statistical measure of the color or intensity valuefor various regions of the test platform that may or may not containtest or control areas and creating at least a 1D array containing thesevalues; if necessary, determining a low-frequency variation in color orintensity value over the array and, if necessary, performingillumination correction and background subtraction; detecting a peak orvalley in the adjusted array corresponding to the test and controlregions to be measured; determining a depth, width, height (for example,based on intensity or color maxima/minima), and/or area (for example,based on integrated color or intensity)) FIG. 19) of these peaks orvalleys which correspond to detection or control regions of the testplatform; and determining a qualitative presence of the selected indiciaof the analyte by the number of peaks or valleys present, and/or aquantitative value of the selected indicia of the analyte byquantitative comparison of two or more peaks or valleys. The embodiedmethod may further be characterized by the following illustrative,exemplary, non-limiting aspects, features, or steps:

-   -   wherein the assay test platform is sensitive to at least one of        a chemical colorimetric reaction, an enzymatic colorimetric        reaction, and a gold nanoparticle colorimetric reaction,        including a lateral flow type immunoassay;    -   wherein the assay test platform is a disposable lateral flow        immunochromatographic test strip;    -   obtaining the image of the at least one test region containing        the analyte and the control region using a smartphone including        a light source and an image detector;        -   comprising using a brand-independent or            operating-system-independent smartphone;        -   further comprising displaying the determined selected            indicia of the analyte on the smartphone;        -   further comprising at least one of time stamping and            location stamping the determined selected quantitative            indicia of the analyte and storing the determined value for            future access;            -   comprising storing the time and/or location data in at                least one of a readable file in the smartphone, an                external readable file, and in a Cloud file;            -   further comprising determining a temporal and/or a                location trend of a plurality of the determined selected                quantitative indicia of the analyte;        -   further comprising correlating the determined selected            quantitative indicia of the analyte to a related selected            metric and displaying a value of the related selected metric            on the smartphone;        -   further comprising providing a smartphone accessory that            includes:            -   a housing that can be removeably attached to the                smartphone in a manner that at least optically couples                the smartphone accessory to a resident smartphone                camera;            -   a lens that allows for adjustment of the focal length of                the smartphone camera to enable imaging of the test                platform in a compact device,        -   wherein the housing is opaque such that the smartphone            accessory is substantially externally light-tight when the            test platform is disposed therein,        -   further wherein the housing includes at least one of a            designed-in optical pathway and a light diffuser in the            housing for providing diffuse illumination of a surface of            the test platform disposed therein from an internal light            source resident in the housing or an external light source            resident in the smartphone to which the smartphone accessory            can be attached;            -   wherein the light source is one of an internal                smartphone flash source and an external LED source;            -   wherein obtaining the image of the test region or                regions containing the analyte and the control region or                regions further comprises illuminating a surface of the                test platform that is illuminated by the light source                with diffused light from the light source;    -   wherein the analyte is one of sweat, saliva, blood, tears,        urine, and other bodily fluids;    -   wherein the step of obtaining the image of the test region or        regions containing the analyte and the control region or regions        comprises illuminating a surface of the modular, colorimetric        test platform;    -   wherein obtaining an image of the at least one test region        comprises obtaining multiple images denoting changes in the        indicia over time, which can be used to provide an improved        estimate of the initial concentration of the analyte;    -   wherein obtaining an image of the at least one test region        comprises obtaining multiple images denoting changes in the        indicia over time, which can be used to serve as a method for        detecting an error with the test.

An embodiment of the invention is a smartphone accessory for use in asmartphone-based point-of-collection, colorimetric-based, quantitativemeasuring system. The smartphone accessory includes a housing that canbe removeably attached to the smartphone in a manner that at leastoptically couples the smartphone accessory to a resident smartphonecamera, wherein the housing is opaque such that the smartphone accessoryis substantially externally light-tight when a test strip is disposedtherein, further wherein the housing includes at least one of adesigned-in optical pathway and a light diffuser in the housing forproviding diffuse illumination of a surface of the test strip disposedtherein from an internal light source resident in the housing or anexternal light source resident in the smartphone to which the smartphoneaccessory can be attached. The embodied smartphone accessory may furtherbe characterized by the following illustrative, exemplary, non-limitingaspects, features, or limitations:

-   -   wherein the designed-in optical pathway in the housing comprises        a wall that creates an indirect optical path between the        external light source resident in the smartphone to which the        smartphone accessory can be attached and a resident smartphone        camera in the smartphone to which the smartphone accessory can        be attached;    -   wherein the light diffuser is disposed intermediate the external        light source resident in the smartphone to which the smartphone        accessory can be attached and a non-colorimetric-reactive region        of the test strip when the test strip is disposed in the        housing;    -   wherein the at least one of the designed-in optical pathway and        the light diffuser is disposed in a manner to provide diffuse        illumination of a rear surface of the test strip;    -   further comprising a light source disposed in the housing; a        light diffuser disposed intermediate the light source and a        resident smartphone camera in the smartphone to which the        smartphone accessory can be attached, in a manner to provide        diffuse illumination of a rear surface of a test strip when the        test strip is disposed in the housing; and a power source for        the light source, disposed in the housing.

An embodiment of the invention is a smartphone accessory for use in asmartphone-based point-of-collection, system. In an exemplary aspect,the system includes a housing that can be removeably attached to thesmartphone in a manner that at least optically couples the smartphoneaccessory to a resident smartphone camera; a lens that allows foradjustment of the focal length of the smartphone camera to enableimaging of the test strip in a compact device, wherein the housing isopaque such that the smartphone accessory is substantially externallylight-tight when a test strip is disposed therein, further wherein thehousing includes at least one of a designed-in optical pathway and alight diffuser in the housing for providing diffuse illumination of asurface of the test strip disposed therein from an internal light sourceresident in the housing or an external light source resident in thesmartphone to which the smartphone accessory can be attached. Theembodied smartphone accessory may further be characterized by thefollowing illustrative, exemplary, non-limiting aspects, features, orlimitations:

-   -   wherein the designed-in optical pathway in the housing comprises        a wall that creates an indirect optical path between the        external light source resident in the smartphone to which the        smartphone accessory can be attached and a resident smartphone        camera in the smartphone to which the smartphone accessory can        be attached;    -   wherein the light diffuser is disposed intermediate the external        light source resident in the smartphone to which the smartphone        accessory can be attached and a non-colorimetric-reactive region        of the test strip when the test strip is disposed in the        housing;    -   wherein the at least one of the designed-in optical pathway and        the light diffuser is disposed in a manner to provide diffuse        illumination of a surface of the test strip;    -   further comprising:        -   a light source disposed in the housing;        -   a light diffuser disposed intermediate the light source and            a resident smartphone camera in the smartphone to which the            smartphone accessory can be attached, in a manner to provide            diffuse illumination of a surface of a test strip when the            test strip is disposed in the housing; and        -   a power source for the light source, disposed in the            housing.

An embodiment of the invention is a portable, modular,point-of-collection, colorimetric-based diagnostic system. Illustrativelimitations include a smartphone including a light source and an imagedetector; a smartphone accessory that can be removeably coupled to thesmartphone, wherein the smartphone accessory is adapted to receive amodular, colorimetric test strip in a manner that exposes a surface ofthe test strip to a light output from the light source, further whereinthe smartphone accessory is substantially light-tight when the teststrip is disposed therein so as to enable consistent internalillumination conditions independently of any external conditions; and anexecutable application resident in the smartphone that, in operation,performs the following steps: acquires an image of at least a portion ofthe test strip; stores the image as an RGBA byte array; splits the imageinto a test image and a calibration image; for the calibration image:extracts a calibration array of pixels; determines a median RGBA colorvalue for the calibration array of pixels; converts the median RGBAcolor value for the calibration array of pixels to a calibrationHue-Saturation-Luminosity (HSL or HSV) color space value; adjusts thecalibration HSL or HSV color space value to a calibration indicia of aselected quantitative indicia of an analyte to be measured; and for thetest image: extracts a test array of pixels; determines a median RGBAcolor value for the test array of pixels; associates the median RGBAcolor value for the test array of pixels to the calibration HSL or HSVcolor space value; and determines a quantitative value of the selectedindicia of the analyte to be measured. The embodied system may furtherbe characterized by the following illustrative, exemplary, non-limitingaspects, features, or limitations:

-   -   wherein the light source is an internal flash source of the        smartphone;    -   wherein the light source is an LED disposed in the smartphone        accessory, further comprising a battery in the smartphone        accessory to power the LED;    -   wherein the system is smartphone platform-independent;    -   wherein the smartphone accessory is an unpowered component;    -   wherein the smartphone accessory includes a light diffuser        and/or a light-diffusing pathway so as to ensure a uniform and        repeatable illumination of at least a desired region of the        modular, colorimetric test platform and which provides a        uniform, diffuse light exposure from the light source to a rear        surface of the test strip;    -   a colorimetric reactive test strip that is removeably disposable        in the smartphone accessory;        -   wherein the colorimetric reactive test strip includes a            colorimetric reactive test region and a non-colorimetric            reactive calibration region;            -   wherein the colorimetric reactive test region is at                least one of chemically colorimetric reactive,                enzymatically colorimetric reaction, and gold                nanoparticle colorimetrically reactive;        -   wherein the colorimetric reactive test strip includes a            light diffuser;            -   wherein the light diffuser is one of a PDMS membrane and                an adhesive tape disposed on at least a portion of a                surface of the test strip;            -   wherein the light diffuser is disposed on the at least a                portion of a surface of the test strip is such a manner                to provide diffuse illumination to a rear surface of the                test strip;        -   wherein the non-colorimetric reactive calibration region            comprises a glossy material.

An embodiment of the invention is a portable, modular,point-of-collection, colorimetric-based diagnostic system. In anexemplary aspect, the system includes a smartphone including an imagedetector; a smartphone accessory as described herein above; and anexecutable application resident in the smartphone that, in operation,performs the following steps: obtaining an image of the at least onetest region containing the analyte and the control region; selecting anarray of pixels in the image of the at least one test region containingthe analyte and the control region; determining a RGBA color value foreach of the arrays of pixels; extracting a test image region foranalysis; converting the RGBA array to an alternate color space asdetermined by the specific test including but not limited to HSL, HSV,or greyscale; determining a median color or intensity value for thepixels in each row, and creating at least a 1D array containing thesevalues; determining a low-frequency variation in color value over thearray and performing illumination correction and background subtraction;detecting a peaks or valley in the adjusted array corresponding to thetest and control lines to be measured; determining a depth or height(intensity maxima/minima) and/or area (integrated intensity) (FIG. 19)of these peaks which correspond to detection lines of the test strip;and determining a qualitative presence of the selected indicia of theanalyte by the number of peaks present, and/or a quantitative value ofthe selected indicia of the analyte by quantitative comparison of two ormore peaks. The embodied system may further be characterized by thefollowing illustrative, exemplary, non-limiting aspects, features, orlimitations:

-   -   wherein the light source is an internal flash source of the        smartphone;    -   wherein the light source is an LED disposed in the smartphone        accessory, further comprising a battery in the smartphone        accessory to power the LED;    -   wherein the system is smartphone platform-independent;    -   wherein the smartphone accessory is an unpowered component;    -   further comprising a colorimetric reactive test strip that is        removeably disposable in the smartphone accessory;        -   wherein the colorimetric reactive test strip includes at            least one test region and a control region;        -   wherein the colorimetric reactive test region is at least            one of chemically colorimetric reactive, enzymatically            colorimetric reaction, and gold nanoparticle            colorimetrically reactive, including a lateral flow type            immunoassay;            -   wherein the light diffuser is disposed on the at least a                portion of a surface of the test strip is such a manner                to provide diffuse illumination to a surface of the test                strip.

Additional features and advantages of the invention will be set forth inthe detailed description to follow, and in part will be readily apparentto those skilled in the art from that description or recognized bypracticing the invention as described herein, including the detaileddescription which follows, the claims, as well as the appended drawings.

It is to be understood that both the foregoing general description andthe following detailed description are merely exemplary of theinvention, and are intended to provide an overview or framework forunderstanding the nature and character of the invention as it isclaimed. The accompanying drawings are included to provide a furtherunderstanding of the invention, and are incorporated in and constitute apart of this specification. The drawings illustrate various embodimentsof the invention and together with the description serve to explain theprinciples and operation of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will be more fully understood and appreciated byreading the following Detailed Description in conjunction with theaccompanying drawings, in which:

FIG. 1 illustrates the steps of a method for obtaining apoint-of-collection, selected quantitative indicia of an analyte on atest platform, according to an embodiment of the invention;

FIG. 2A shows the steps of extracting the hue, saturation and luminosityof both a reference area and a detection area on a test strip, andquantifying an analyte concentration using a calibration curve, similarto that of FIG. 1; FIG. 2B shows the relationship between differentanalytes and hue, saturation and luminosity parameters, according to anillustrative embodiment of the invention;

FIG. 3A shows an overview of a modular smartphone ‘app’ and itsoperation, in which the user selects the desired test strip from a menuof pre-calibrated test options; FIG. 3B the app automates the process ofimage acquisition and processing for the desired application. The topimage shows a sweat pH and electrolyte interface and the bottom imageshows a salivary monitoring interface; FIG. 3C a plot of the data isproduced to demonstrate trends over time, according to an illustrativeembodiment of the invention;

FIG. 4A schematically shows three designs for creating uniform lightingwithin a smartphone accessory holder: a wall is provided to create anindirect optical path from the flash to the test strip and the camera;FIG. 4B a LED is placed within the cavity behind a diffuser to generatelow-power, uniform light to illuminate a rear surface of a test strip;FIG. 4C is an optically diffusive material is placed in front of thecamera flash to spread the light from the flash uniformly around theaccessory cavity to illuminate a rear surface of a test strip, accordingto illustrative aspects of the invention;

FIG. 5A schematically shows a smartphone accessory mounted on asmartphone including a test strip inserted therein; and FIG. 5B shows across sectional view of the accessory for providing uniform illuminationof a rear surface of a test strip to allow the test strip to be imagedconsistently in different external lighting conditions, according to anillustrative aspect of the invention;

FIG. 6 schematically shows a disposable test strip used for pHmeasurements. The strip contains four colorimetric patches that can becompared for accurate pH measurements, and two constant colors forcalibration, according to an illustrative aspect of the invention;

FIG. 7A shows a test strip consisting of two different areas that areimaged using the smartphone's camera: a gold nanoparticle-baseddetection area and a reference area. The detection area allows for acolorimetric reaction to occur when a sample of, e.g., sweat, saliva orblood is applied. The reference area consists of a uniform piece ofpolymer that does not change color when the sample is applied, accordingto an illustrative aspect of the invention; FIG. 7B shows a variation inpredicted concentration at different AuNP-anti-25(OH)D₃ incubation timeson the detection area for 0 nM sample 25(OH)D, according to anillustrative aspect of the invention;

FIG. 8A shows a battery powered smartphone accessory with LED lightsource, on an iPhone, with the inset showing the components of theaccessory; FIG. 8B is a FT-IR spectra showing the chemical compositionof the APTES, maleic anhydride, and aminopropylated 25(OH)D₃ layers thatconstitute the detection area of an illustrative test strip forquantitative Vitamin D measurements, according to an illustrative aspectof the invention;

FIG. 9A and FIG. 9B, respectively, show a 3D printed black polymer teststrip support and a test strip containing a pH indicator region, areference region, and a light diffusive material. FIG. 9C shows asmartphone accessory; all according to an illustrative aspect of theinvention;

FIG. 10A illustrates the merits of the HSV color space: The hue valuegives the color as an angle transitioning from red through blue(counterclockwise); FIG. 10B The hue increases monotonically withincreasing pH and is linear over a large pH range; according to anillustrative aspect of the invention;

FIG. 11A schematically illustrates a nanoparticle based colorimetrictest strip with details of a competitive Vitamin D assay including bloodfiltration; FIG. 11B shows a more detailed view of stages two and threefrom FIG. 11A, according to an exemplary aspect of the invention;

FIG. 12A shows colorimetric variation on the test strip of FIG. 11 atdifferent known 25(OH)D concentrations; FIG. 12B calibration curveshowing brightness difference between the detection area and referencearea AH at different known 25(OH)D concentrations; FIG. 12C shows analgorithm used in quantifying 25(OH)D levels on test strip, according toan illustrative aspect of the invention;

FIG. 13A shows a picture of a smartphone accessory and the test stripused; the inset shows the inside of the accessory with a black PDMSdiffuser; FIG. 13B shows a variation in saturation across a 200 px areain the center of a low cholesterol (<100 mg/dl) test strip for differentdiffusers in the accessory; FIG. 13C shows variation in lightness acrossa 200 px area between the low cholesterol strip (<100 mg/dl) and highcholesterol (>400 mg/dl) strip for two different diffusers. FIG. 13Dshows typical smartphone acquired images of the colorimetric reaction,at low (<100 ma/dl) and high (>400 mg/dl) cholesterol concentrations,according to an illustrative aspect of the invention;

FIG. 14A shows variations in predicted cholesterol levels vs. time for atest strip with the solid horizontal line representing the actualcholesterol level of 178 mg/dl; FIG. 14B shows variation in readingswith different three different iPhones. FIG. 14C shows the imaging ofthe test strip during the first 40 s; according to an illustrativeaspect of the invention;

FIG. 15A shows variation in lightness (13) and saturation (black) vs.cholesterol levels; FIG. 15B predicted cholesterol concentration versusactual cholesterol concentration defined by CardioCheck PA, according toan illustrative aspect of the invention;

FIG. 16A shows a smartphone accessory assembled; FIG. 16B shows a frontside showing the battery placement; FIG. 16C shows a back side showingthe LED, lens, switch and diffusor incorporation, according to anexemplary aspect of the invention for qualitative and/or quantitativereadout of lateral flow immunochromatographic assays, and associatedmethods and applications;

FIG. 17A illustrates operation of the smartphone based system forqualitative and/or quantitative readout of lateral flowimmunochromatographic assays: hardware; FIG. 17B software;

FIG. 18A schematic of the image processing algorithm. The raw image isfirst filtered to reduce the signal-to-noise ratio, then transformed toHSL so the hue can be used for line detection. The image is then reducedto one dimension with a row-wise median filter, and the local minima aredetected in the 1D signal. The shape and height of the found peaks canalso be analyzed to give a quantitative comparison of the test andcontrol lines; FIG. 18B positive test result—the raw image of the teststrip taken with the device and the processed data with two detectedminima; FIG. 18C negative test result—the raw image of the test striptaken with the device and the processed data with one detected minimum,according to an illustrative embodiment of the invention; and

FIG. 19 is a graph showing test and control (T/C) line comparisons alongmultiple dimensions, according to an illustrative aspect of theinvention.

DETAILED DESCRIPTION OF NON-LIMITING, EXEMPLARY EMBODIMENTS OF THEINVENTION

Embodiments of the invention are methods, apparatus, and systemspertaining to obtaining and presenting (i.e., displaying orcommunicating out) quantitative, colorimetric-based measurements oftarget analytes using a smartphone platform that are accurate,consistent and reliable independent of the smartphone platform beingused. The achievement of accurate, consistent and reliable quantitativemeasurements of target analytes is possible with the use of commerciallyavailable test strips on which a deposited target sample (e.g., saliva,sweat, blood, urine, others) can undergo a colorimetric reaction (e.g.,chemical colorimetric reaction, enzymatic colorimetric reaction,nanoparticle colorimetric reaction) initiated by diffuse illumination ofthe test strip, image recording by the smartphone camera, and imageprocessing within the smartphone by a resident software application(‘app’). More particularly, the embodied invention includes a removable(or detachable from a smartphone) smartphone accessory into which thetest strip is disposed. The smartphone accessory provides an internalenvironment that is light-tight such that essentially all light not usedfor imaging the test strip and colorimetric reaction is excludedregardless of ambient conditions, as well as an illumination modality inthe form of a designed-in optical pathway or a light diffuser thatinsures a consistent optical and imaging environment for every teststrip, thus rendering the embodied system and methodsmartphone-platform-independent.

Exemplary embodiments of a smartphone-based method, a smartphone system,a smartphone app, a smartphone accessory and, where relevant, a teststrip, are described in detail herein below. While the disclosuredescribes examples of target analytes of vitamin D, sweat, saliva, pHand cholesterol, other analytes as listed in Table 1, and others notlisted but understood by those skilled in the art, may likewise besimilarly measured.

The colorimetric test strips utilized in conjunction with the embodiedinvention are not necessarily part of the invention per se, althoughthey play a significant role in the operability and enablement of theembodied invention. In this regard, the colorimetric-reactive testregion on the test strips disclosed herein are for the most partcommercially available and may already appear on test strips that mayalso include a calibration or reference (non-colorimetric-reactive)region on a (typically front) surface thereof. The test region of thetest strips contains the appropriate chemistry to enable a colorimetricreaction that may include a chemical colorimetric reaction, an enzymaticcolorimetric reaction, or a (e.g., gold) nanoparticle colorimetricreaction.

Various exemplary test strips suitable for use in conjunction with theembodied invention are illustrated in FIGS. 6, 7, 9 b, 11 and 12.Examples of the embodied invention will now be described in conjunctionwith these various test strip modalities.

FIG. 9( b) shows an early proof of concept test strip that contains a pHindicator (test) region for measuring a sweat sample, a referenceregion, and a light diffusive material, as shown. This test strips isshown assembled on a 3D printed black polymer support in FIG. 9( a) foruse in a smartphone accessory (holder) as illustrated in FIG. 9( c). Thedimensions of this test strip are about 1 cm×2 cm and were designed tofit the illustrated holder. The test strip and holder were optimized fordata acquisition with the camera of an iPhone 4. The pH indicator paperstrip was chosen to cover the physiological range of pH values (pH 5 topH 8). The pH paper was cut in 0.5 cm by 1 cm strips and inserted in theholder through the side. The reference paper strip was chosen to aid inthe calibration of the measurements and was a green glossy referencepaper. Green falls within the range of color variation for the pH paper,while the glossy nature of the paper ensured that the color of thereference did not change when the strip comes in contact with sweat. Thelight diffusive materials that were used were PDMS and adhesive tape.Adhesive tape offered a simple fabrication procedure and robustness ofthe assembled test strip. In the system illustrated in FIG. 9( c), theresident flash of the cell phone camera was used to illuminate the teststrip. The light diffuser was incorporated between the flash and thetest strip in order to distribute the light from the flash evenly acrossthe surface of the test strip. The test strip shown in FIG. 9( b)redirected light from the flash to diffusely illuminate the rear surfaceof the test strip.

In this example, sweat was collected from the forehead of a user afterexercising for 5 to 10 minutes. The test strip was used to directly wipethe sweat off the forehead with the pH indicator paper in direct contactwith the sweat for about five seconds to ensure that the pH indicatorpaper was fully and uniformly soaked with sweat. Once the sweat wascollected, the user opens the optical holder and introduces the teststrip with the pH indicator paper facing the smartphone camera as shownin FIG. 9( c). After closing the optical holder such that there is noexternal light reaching the test strip, the user waited about one minutebefore taking the measurement to allow the pH indicator paper to reach auniform and stable color. The user then takes a photo-image using thesmartphone's camera and a resident smartphone application is used toobtain quantitative pH and sodium concentration values.

The smartphone software application was used to both image thecolorimetric test strip and determine the pH of the sample. Upon openingthe application, the user is prompted to place the used test strip intothe strip holder accessory behind the camera. After loading the strip,the user presses a “Camera” button, and the smartphone camera takes aphotograph of the strip for image processing. When the user runs the“Analysis” function, the application then stores the photograph into anRGBA byte array so that the red, blue, green, and alpha (transparency)values for each pixel can be accessed independently. The alpha channelcan be discarded as it does not vary with analyte concentration.

The camera image is split into sections, with one section containing thesample to be measured and additional sections for each of the (one ormore) calibration colors, and a 256×256 array of pixels is selected ineach section for analysis. The median color of each of these 256×256pixel segments can then be determined separately. Looping through thebyte array, the red, green, blue, and alpha values are extracted andstored for each pixel in a given region, and then stored in additionalarrays. These arrays are then sorted in ascending order and the medianvalue is selected for each color channel. The median value is usedinstead of an averaging function because of the nature of RGBA values; asmall number of white pixels (with R, G, and B values of 255) would havea minimal impact on a median color value, but could greatly distort themean.

For standard pH indicator materials, it is not possible to determine thepH value from only one of the three RGB channels; moreover, an increasein the measured value of any one channel (e.g., only red) does notcorrespond to a linear increase in the pH of the sample. To simplifyanalysis and improve accuracy, the measured color can be transformedinto an alternative color space that matches more closely to theindicator color trends. The median RGBA value for each 256×256 array isconverted to the Hue-Saturation-Luminosity (HSL) color space by thestandard conversion algorithm. In the HSL color space, the hue value isa single measurement from 0-360 that has been determined experimentallyto vary approximately linearly with pH for common universal indicatormaterials (see FIG. 10).

For translation of the HSL values to the corresponding pH values, acalibration curve was determined using many titrations of buffers withknown pH values. By comparing the median HSL value to this calibrationcurve, the pH of a sample can be reliably determined from the measuredcolor. Because the holder shields the camera from external lightfluctuations, the lighting conditions should in principle not varygreatly from image to image. Nevertheless, calibration data was used toaccount for the fluctuations that might inevitably persist, as well asto account for differences between individual smartphone cameras. Forthis reason, calibration sections were included in the disposable teststrip that do not vary in color with changing pH. By analyzing thesesections separately as described above, the HSL value for a calibrationcolor can be determined on each measurement and compared directly withthe expected value from the initial calibration. Due to the linearity ofthe pH with increasing H value, the calibration curve can be shifted toaccount for this difference, and the HSL-to-pH conversion for the samplesection can be made more accurate. This calibration can be doneaccurately with a single calibration color, but additional calibrationcolors in other parts of the spectrum can be used for applications whichrequire very high degrees of accuracy.

After the median HSL value is ultimately converted to pH with thecalibration, this final pH value can be time- (and/or location-) stampedand stored in an external data file on the smartphone, which can be readin by the application later. Depending on the specific application, thepH measurement can also be correlated to another metric of interestprior to display and further analysis; for instance, for sweat hydrationanalysis, empirical testing of sweat composition in the literature hasdemonstrated a strong (r=0.79) correlation between pH and sweat sodiumconcentration. As reported, sodium concentration can be interpolatedlinearly from pH by pH=4+0.04*[Na+] (where the concentration in ismillimolar). Similar relationships exist to correlate measured pH with anumber of important metrics for both sweat and saliva analysis, and thisfinal step can be easily modified accordingly so that the software canfunction in multiple diverse applications. FIG. 1 illustrates theexemplary method in a flow chart.

Advantageously, the entire process, from swiping the disposable strip tocollect the sample through receiving the pH and/or sodium concentrationmeasurement, need take only a few seconds, and the results can displayedon the smartphone screen for immediate user feedback. Because the datacan also be time-stamped and stored, all of the measurements from agiven run can be retrieved and the trend of the pH over time can bedetermined for additional information.

In addition to sweat, saliva is another body fluid that can provideimportant information on the user's health state. The pH of saliva, forexample, has been shown to be influenced by diet. Monitoring salivary pHcan be useful in preventing caries and maintaining good dental hygiene.Salivary pH can be measured in the same way and using the same device asfor sweat pH. In addition, the calcium concentration in saliva can be anindicator of periodontitis, thus an embodied device could be used dailyor routinely to monitor salivary pH and calcium concentration in orderto maintain good dental hygiene.

Another application for a pH type device is for drug and alcohol abusemonitoring. For example, cocaine can be detected in sweat or salivausing several chemical and biochemical tests. Ethanol and fatty acidethyl esters can also be monitored using chemical tests. This wouldallow users and health care professionals to track desintoxicationprogress and to monitor the risks of drug and alcohol abuse.

Another application is for the chemical detection of glucose in saliva.Glucose detection in saliva can be used as a fast, non-invasive test forpeople with potential risk of diabetes. This would allow people who havehigh blood glucose concentration to monitor their daily salivary glucoselevels and adjust their diet accordingly.

Chemical tests can also be used to determine the presence of amino acidsin sweat. This application could be important for detecting atopic skinconditions that might develop. Other areas of testing that currentlyrely on colorimetric pH indicator strips include soil testing, watertesting for aquariums and swimming pools, and chemical experiments insecondary and tertiary education.

FIG. 6 illustrates a disposable test strip 200 having a test region thatcontains four separate colorimetric pH indicator regions 202, 203, 204,205 and two constant colored plastic reference patches 208, 209 that donot vary with pH, which are used to calibrate away differences in lightintensity and camera function from smartphone platform to smartphoneplatform.

Changes in light intensity while exercising can significantly change thecolorimetric measurements made with the camera. It was found that thebest way to maintain light uniformity while collecting data is toincorporate a light source in the system. There are three differentmethods/designs that are used to provide uniform illumination to thecamera during data acquisition as illustrated in FIG. 4( a, b, c). Asmartphone accessory housing 500 is shown in a cross sectional top planview operationally attached to a smartphone. A first design shown inFIG. 4( a) provides a designed-in, indirect optical path that redirectsthe light from the resident smartphone flash 302 around a partial wallstructure 348 in the housing so as to illuminate the rear surface 1002of the test strip with diffuse light. An alternate design shown in FIG.4( c) also makes use of the resident flash 302 of the smartphone toilluminate the test strip 1000. A light diffuser 308 is incorporatedbetween the flash 302 and the front surface 1004 of the test strip inorder to distribute the light from the flash evenly across the frontsurface of the test strip containing the test region 1008. A thirddesign shown in FIG. 4( b) makes use of an LED 351 mounted in thehousing 500 behind the test strip 1000 with a light diffuser 308disposed between the LED and the rear surface 1002 of the test strip.The test strip illuminated uniformly with diffuse light. In this design,a battery 355 in the smartphone accessory provides external power to theLED 351 as illustrated in the inset in FIG. 8( a).

Another example of a smartphone system and method for quantitativelymeasuring salivary pH and sweat pH is presented. In this example, thetest strips incorporate three different elements inserted in a 3Dprinted support: an indicator strip, a reference strip and a flashdiffuser. The indicator strip consists of a 9 mm by 4 mm cutout of apHydrion Spectral 5.0 to 9.0 plastic pH indicator strip for sweattesting and a 1.0 to 14.0 strip for saliva testing. The reference stripis made of white plastic material and is used in order to detect changesin white balance on the iPhone camera due to different light conditionsor user error. The flash diffuser consists of a 2 mm thick membrane ofpolydimethylsiloxane (PDMS). Other suitable diffuser materials can alsobe used. The purpose of the flash diffuser is to reduce variations inthe reading for different lighting conditions. It allows light from thesmartphone's flash to diffuse and illuminate the rear surface of thetest strip uniformly. In addition, the accessory is 3D printed usingopaque Vera black material in order to isolate the test strip fromvariable external light.

The software app is illustrated in FIGS. 1 and 3 works as follows:First, upon loading the app, the user selects the test strip being usedfrom a menu of different biomarker tests available, and the app loadsthe appropriate calibration data and user interface. Secondly, the userinserts the disposable test strip into the smartphone accessory andtouches the “Analyze” function on-screen. Thirdly, the app turns on thecamera flash and takes an image of the test strip. The quantitativeanalyte concentration is colorimetrically determined from the image anddisplayed on screen in under five seconds. If pertinent to the specificanalyte, additional post-processing is also done from the results, andthese results are displayed alongside the analyte concentration.Finally, by swiping left, a scatter plot of the results is generated toshow trends over time. If desired, the data set can also be sent viaemail for later viewing or additional analysis.

Although the ubiquity of smartphones with high-quality integratedcameras makes such devices ideal for point-of-care biomarker detection,the wide range of variations across different devices and of test stripillumination present significant challenges to accurate colorimetricquantification. Other investigators have addressed this problem bycalibrating for ambient light conditions through conversion to colorspaces which are less sensitive to changes in brightness. On its own,this approach still requires uniform external illumination, and falsecolorimetric readings can be made if the smartphone is not placed at theproper distance from the test strip. One of the unique opportunities ofsmartphone-based colorimetric detection for portable diagnostics,however, is that image acquisition can instead be automated, so that thetest strip is always held in the ideal position and imaged in the samemanner, and the data is not easily affected by deviations in userprotocol. Our device is isolated from ambient light with the smartphoneaccessory (e.g., FIG. 5 a) and diffuses light from the smartphone cameraflash for reproducible and uniform illumination, improving measurementaccuracy and minimizing the potential for user error.

Similarly as stated above, although the image from the smartphone camerais initially defined with RGB (red green blue) values, individual red,green, and blue channels do not correlate well with pH over the range ofa universal indicator strip. Nevertheless, the RGB values can be readilyconverted to an alternate color space that matches the color spectrum ofthe test strips more closely. We chose to convert to hue, which unlikeRGB was found to monotonically increase with pH in our experiments overthe entire range of the colorimetric test strips used. After an initialcalibration to determine the relationship between the hue and theanalyte concentration for each test strip, this single hue value issufficient to quantitatively specify the color with a high degree ofaccuracy.

The process of image analysis is as follows. When the “Analyze” buttonis pressed, the smartphone app activates the camera flash, and an imageis captured and stored first as an RGBA (red green blue alpha) bytearray. The alpha channel, which is a measure of transparency, isdiscarded as it does not vary with analyte concentration. The RGB arrayis split into two sections—the first, corresponding to the uppercolorimetric test strip, and the second, to a lower reference region ofknown color value which is used to compensate for variations betweendifferent smartphone cameras and from automated camera adjustmentfunctions such as white balance. A 256×256 pixel square is selected fromthe center of each of these sections, and the hue value is calculatedfor each pixel from the RGB channels. The hue values are sorted, and themedian value is chosen to minimize any remaining edge effects which arenot removed by the PDMS flash diffuser. Because the color of the plasticreference section should not change between experiments if the deviceworks correctly, the image acquisition process is restarted if thereference hue value varies from the expected calibration value by morethan 5. This serves to eliminate the possibility of a user protocolerror—if the test strip is inserted incorrectly and the strip is notoptically isolated, the reference check will fail and the data will notbe stored. If the reference check is passed, the test hue value isconverted into an analyte concentration by means of a measuredcalibration curve and the relevant biological information is displayedon-screen immediately. A schematic of this process is shown in FIG. 1.

The correlation between hue and pH is built into the application,allowing users to run tests without additional calibration. This ispossible because the accessory is designed in a way that minimizes theeffect of external lighting as was previously discussed. FIG. 5 billustrates the design of the accessory housing around the camera andflash that allows for uniform lighting of the test strip. By guiding theflash light through the PDMS diffuser on the strip and behind the teststrip, we avoid the need to build in a lighting element, such as an LED,that would make the system bulkier and require power input. The strip isimaged at a distance of 2.20 mm from the smartphone's camera and thewhole optical piece has a depth of 4.90 mm. The relationship between hueand pH for our test strips was established using buffer solutions and apH electrode (VWR SympHony SB70P) for an 8 point calibration. A thirdorder polynomial was fitted through the data points in order to obtain acorrelation between

pH and hue. It was found that the variation between phones is thelargest source of error, therefore defining the accuracy of the systemover the range of physiologically relevant pH values to be within 0.2 pHunits was useful.

In order to further improve the accuracy of our system, we incorporate awhite reference strip on our test strip. A large variation in the huevalue of the white reference indicates a failed measurement, possiblyfrom a faulty or incorrectly inserted test strip. If the applicationdetects an abnormal hue value, it rejects the data point and signals tothe user to take another reading.

Although the system disclosed here was designed for and prototyped onthe iPhone 4 and 4S, it could easily be ported to any other smartphoneplatform with a CMOS camera. Even if there are systematic differences incamera function and sensitivity between smartphones from differentmanufacturers, these differences can be corrected by calibrating thehue-to-pH conversion function once for each smartphone model used. Ifthe hardware accessory is re-designed to fit over the camera andproperly re-calibrated, the most important metric for determining theaccuracy of the device should still be the variation between severalphones of the same model, as described above.

FIGS. 7( a), 9(a) and 9(b) illustrate gold nanoparticle (AuNP)-basedtest strips used to quantitatively measure vitamin D levels in a sampleusing a colorimetric competitive direct-antigen immunoassay according toan aspect of the embodied invention. This assay enables thequantification of 25(OH)D molecules whose small size (˜400 g/mol)restricts their binding to more than one antibody at a time. 25(OH)Dlevels can be quantified by evaluating brightness differences betweenthe detection area and a reference area on the test strip. Thesmartphone system can be used to quantify vitamin D levels by evaluatingserum samples with unknown 25(OH)D concentrations.

FIG. 8( a) illustrates an exemplary smartphone system that includes asmartphone 2000 loaded with a smartphone app and a smartphone accessory500 attached to the smartphone. As described above, the smartphoneaccessory has been designed to minimize the effect of variability inexternal lighting conditions with an LED used to uniformly diffuselyilluminate the rear surface of the test strip. The test strip 1002 wasconstructed and is composed of a detection area and reference area asillustrated in FIG. 12( c). The reference area allows the algorithmoutlined in FIG. 12( c) to further adjust to differences in differentsmartphone platforms. The detection area that enables the colorimetricreaction to occur comprises a surface-immobilized layer of 25(OH)D on afused Si-based substrate that serves as the detection area on the teststrip. As shown in FIG. 8( b), 3-aminopropyltriethoxysilane (APTES) andpolystyrene-co-maleic anhydride (PSMA) layers were sequentially coatedon the fused Si substrate and aminopropylated 25(OH)D was covalentlylinked to achieve a stable 25(OH)D coating. In order to validate thismethod, the surface treatments were characterized by Fourier-transforminfrared spectroscopy (FT-IR) as shown in the graph in FIG. 8( b). Theinitial introduction of APTES layer on the Si substrate is evident fromthe transmittance peak at 1654 cm′ that is associated with primary aminegroups (—NH₂). The PSMA coating was confirmed by the appearance of peaksat 1850 and 1780 cm⁻¹, which have been linked with maleic anhydrides inother studies. Lastly, the peak at 3300 cm⁻¹ corresponds to theformation of the secondary amine (R₂NH) bond between the PSMA andaminopropylated 25(OH)D and verifies the 25(OH)D immobilization.

The colorimetric reaction on the detection area of the test strip isbased on a surface-based gold nanoparticle-based immunoassay asillustrated in FIGS. E(a) and 7. When a sample is applied onto thedetection area of the test strip, only the antibody conjugates that arenot bound to the 25(OH)D present in the initial sample are captured bythe coated 25(OH)D on the surface. The colorimetric signals from theimmobilized AuNP-antibody conjugates are then amplified using a silverenhancement scheme as the silver ions undergo reduction on the surfaceof the AuNP to increase their size and thereby increase the limit ofdetection of the system. For samples with high vitamin D levels, most ofthe antibody conjugates are occupied with 25(OH)D from the initialsample, resulting in only a subtle change in the colorimetric signal onthe test strip. For samples with low vitamin D levels, the test stripdevelops an intense color that reflects the high number of antibodyconjugates bound on the surface.

A critical step during testing is the incubation of theAuNP-anti-25(OH)D sample solution on the test strip's detection area. Itis important to characterize the time it takes for the AuNP-anti-25(OH)Dto immobilize in order to minimize the total assay time and to improveaccuracy. In FIG. 7( b), we show the effect of different incubationtimes on the brightness difference between the detection and referenceareas of the test strip (ΔH) for a sample without 25(OH)D. After 6 h thebrightness difference is within 10% of that obtained after a typical 12h overnight incubation. This indicates that a 6 h incubation time issufficient in order to obtain accurate results during such vitamin Dmeasurements. The incubation time can however be significantly reducedby using the obtained negative exponential relationship to determine theminimum incubation time for ensuring that sufficient conjugate bindingevents have occurred on the detection area.

Once the competitive binding of AuNP-anti-25(OH)D was performed on thetest strip, the quantification of the 25(OH)D levels in the initialsample can be achieved using the smartphone platform. First, thecolorimetric change is captured using the smartphone's camera afterinserting the test strip in the smartphone accessory. In FIG. 12( a) weshow the colorimetric change in the detection region at different knownconcentrations of 25(OH)D. By comparing the differences in brightnessbetween the detection area (B_(det)) and reference area (B_(ref)) we canestimate the concentration of 25(OH)D. In FIG. 12( b) we show thatΔH=B_(det)−B_(ref) can be correlated to the 25(OH)D concentration in theinitial sample. A second order polynomial was then fitted onto thiscalibration curve in order to obtain a function such that[25(OH)D]=f(ΔH).

FIG. 12( c) shows the algorithm that allows the quantification of25(OH)D across the entire range of physiological values. First, thedetection area is scanned for silver enhanced regions whereAuNP-anti-25(OH)D is bound. This is important because at higher 25(OH)Dconcentrations in the initial sample, the detection area rarely exhibitsa uniform colorimetric change. A 100 px by 100 px area around the highintensity silver enhanced region is taken and the brightness is averagedacross all the pixels in that area. The same steps are then performed onthe reference region and an average brightness is calculated. Once thebrightness difference between the detection area and the reference areais computed, the algorithm uses a second order polynomial[25(OH)D]=f(ΔH) derived from FIG. 12( b) to calculate the 25(OH)Dconcentration in the initial sample.

For a vitamin D deficiency test, once the sample has been acquired,several steps were performed in solution prior to its application ontothe test strip. First, the filtered serum sample was mixed 1:10 (v/v)with 0.78 g/ml acetonitrile (Thermo Fisher Scientific Inc.) in order toliberate the 25(OH)D molecules that are in proportion of 95-99% bound tovitamin D binding proteins (DBP). The sample was then mixed withAuNP-anti-25(OH)D conjugate solution for 30 min. This ensures that allthe 25(OH)D initially present in the blood sample is bound toAuNP-anti-25(OH)D before being applied onto the test strip.

The spherical AuNP (Nanopartz Inc., 30 nm) came pre-treated withN-hydroxysuccinimide ester terminal (NHS) groups which specificallyreacted with the primary amines of monoclonal anti-25(OH)D₃ IgG(Raybiotech Inc.) to form the AuNP-antibody conjugates. The antibody wasfirst purified using the Pierce Antibody Clean-up Kit (Thermo FisherScientific Inc.) because 2% bovine serum albumin (BSA) stabilizers inanti-25(OH)D₃ are known to interfere with the amine-reactiveconjugation. The antibody solution was placed into the Melon Gel-basedpurification support which binds non-antibody proteins while allowingthe IgG antibody to flow through in a purified form during theone-minute centrifugation at 6000 g. The successful removal of BSA waschecked by performing sodium dodecyl sulfate polyacrylamide gelelectrophoresis (SDS-PAGE). For conjugation, the AuNP were mixed withthe purified anti-25(OH)D₃ at 0.1 mg/ml in 0.01 M amine-free phosphatebuffer saline (PBS) buffer at pH 7.4. The mixture was sonicated for 30 sto re-suspend AuNP into solution, followed by vortexing for 30 min. atroom temperature. The centrifugation was performed at 15000 g for 10min. to remove the excess antibody in supernatant form and the finalconjugates were reconstituted in 0.01 M PBS with 0.1% Tween-20 at pH7.4. The successful conjugation was confirmed through surface plasmonresonance changes using ultraviolet-visible spectroscopy. The conjugateswere diluted to 10 μg/ml and stored at 4° C. until use.

The covalent immobilization of 25(OH)D was achieved by obtaining25(OH)D₃, 3′-Aminopropyl Ether (Toronto Research Chemicals Inc.) andusing its primary amines as linkers to the test strip surface.Immobilization of the peptides to surface using maleic anhydridechemistry has been demonstrated previously by others. Here, theaminopropylated 25(OH)D₃ was immobilized on a flat Si substrate otherthan on a typical well-plate which represents a compatibilityimprovement for use in our smartphone-based detection. Briefly, 4″ fusedSi wafers were cleaned in piranha solution, immersed in 20 mM APTES(Sigma-Aldrich Co. LLC) in isopropanol for 2 h and annealed at 120° C.for 1 h. The APTES coating acted as an activation layer for the bindingof 1% PSMA (Sigma-Aldrich Co. LLC) dissolved in tetrahydrofuron, whichwas spin-coated at 3500 rpm for 30 s followed by curing at 120° C. for 2h. The treated Si wafer was cooled and immersed in acetone for 10 minand subsequently diced into 4 by 7 mm strips. Finally, the 25(OH)Dimmobilization was achieved by incubating the PSMA-treated strips with20 μg/ml aminopropylated 25(OH)D₃ in the coating buffer (0.1 Mcarbonate/bicarbonate buffer at pH 9.4) for 1 h at 37° C. The unreactedPSMA sites were treated by incubating the blocking buffer (0.01 M PBSwith 1 mg/ml Casein and 0.05% Kathon preservative at pH 7.4) for 30 minat room temperature, and cleaned with washing buffer (0.01 M PBS with0.05% Tween-20 at pH 7.4). The incubation procedures were performed inincubation chambers that housed the test strips and prevented pre-maturedrying of the treatment solutions. The modified Si surfaces after eachsurface treatment were characterized by FT-IR using a Vertex 80-vspectrometer (Bruker Optics) equipped with a 60° germanium attenuatedtotal reflection (VeeMax Ge ATR) crystal. For each spectrum, 256 scansat a spectral resolution of 4 cm⁻¹ were performed using a liquidnitrogen detector. After the 6 h incubation of AuNP-antibody conjugateswith the sample on the detection area, the strip was rinsed three timeswith the washing buffer to remove unbound conjugates and incubated withsilver enhancement solution from the Silver Enhancer Kit (Sigma-AldrichCo. LLC). After 20 min, the detection area was rinsed with the washingbuffer and air dried at room temperature.

We have demonstrated that we can measure physiological levels of 25(OH)Din solution with accuracy better than 15 nM and a precision of 10 nM.Moreover, the results obtained using the embodied invention arecomparable with that of commercial ELISA kits. By analyzing three serumsamples with unknown 25(OH)D concentrations, we were able to determineaccurately the extent of vitamin D deficiency in each case.

In the disclosed method, we used a specific form of 25(OH)D for coatingand detection, namely 25(OH)D₃ and anti-25(OH)D₃. The monoclonalanti-25(OH)D₃ has 68% cross reactivity with 25(OH)D₂ and 100% with25(OH)D₃. The use of 25(OH)D₃ for the detection zone coating allows forthe capturing of all the unbound AuNP-anti-25(OH)D₃ conjugates after theinitial interaction with the sample.

An exemplary aspect of the invention is for cholesterol measurement. Theembodied system can quantify cholesterol levels from colorimetricchanges due to cholesterol reacting enzymatically on a dry reagent teststrip. Again, a smartphone accessory allows uniform and repeatable imageacquisition of the test strip, and is used in conjunction with an appthat analyzes parameters such as hue, saturation, and luminosity of thetest area, quantifies the cholesterol levels, and displays the value onthe screen, as described herein.

FIG. 13( a) illustrates the smartphone accessory attached around thecamera of the smartphone. It has been designed to allow quantificationof the cholesterol colorimetric reaction that occurs on a dry reagenttest strip over the entire range of physiological cholesterol values.The smartphone's flash is used to illuminate the strip. The utilizationof the resident light source provides a robust system and the ability todeal with misalignment of the test strip, and it provides more uniformlighting for accurately imaging the colorimetric reaction on the teststrip. Typical smartphone acquired images of the colorimetric reaction,at low (<100 mg/dl) and high (>400 mg/dl) cholesterol concentrations areshown at the bottom of FIG. 13.

In order to improve the sensitivity of the system to variations in thecolor of the test strip and to reduce the effect of test stripmisalignment into the device, we incorporated a light diffuser over theflash as can be seen in the inset of FIG. 13( a). The effect ofintegrating different diffusers in the accessory housing on the measuredsaturation values at different points on the detection area is shown inFIG. 13( b). It can be seen that at low cholesterol concentrations alight diffuser is needed so that the color change can be quantifiable.When no diffuser is used or only PDMS is used, the strips appears aswhite with either 100% or 0% saturation levels. Diffusers made of blackPDMS and FullCure, an acrylic-based photopolymer material, allowed forthe saturation value on the low cholesterol test strip to bequantifiable with standard error of 0.16% and 0.42% respectively acrossa 200 px section at the center of the strip. This is important becauseit indicates that misalignment of the test strip will have little effecton the measured saturation value.

The sensitivity of the image acquisition system, defined as the abilityto differentiate between colorimetric test strips at differentcholesterol concentrations has also been investigated. As can be seen inFIG. 13( c), the accessory with the black PDMS diffuser has on average a36.6% point decrease in lightness when imaging the high cholesterol teststrip compared to the low cholesterol one. The effect is much lower,only 5.2%, when a FullCure diffuser is used. Consequently, black PDMSwas used as the diffuser material because it not only allows for uniformillumination of the strip but also maximizes the range of colorimetricvariation on the strip.

The test strips used in this example are dry reagent strips manufacturedby CardioChek (Polymer Technology Systems Inc, IN, USA). When the userapplies a drop of blood on one side, it first goes through a series offilter papers that separate plasma from red blood cells and direct someof the plasma towards an analyze-specific reaction pad. At that point,HDL is separated from LDL and VLDL fractions and precipitated by thereaction with phosphotungstic acid. An enzymatic reaction then convertstotal cholesterol and HDL cholesterol to cholest-4en-3-one and hydrogenperoxide. The peroxide then reacts with disubstituted aniline to formquinoneimine dyes7. The color change from the last reaction is thenimaged inside the smartphone accessory by the smartphone camera.

In order to quantify the colorimetric reaction and to obtain the bloodcholesterol concentration value, we developed a calibration curvelinking cholesterol to the HSL (Hue Saturation Lightness) cylindricalcoordinate representation of the RGB (Red Green Blue) color values atthe center of the cholesterol test strip. Hue (II) has a piecewisedefinition and in the region of interest of the cholesterol colorimetricreaction can be written as a function of the red (R), green (G) and blue(B) color values:

H=(B−R)/C+2 if M=G or H=(R−G)/C+4 if M=B.

In the equation above, C=M-m where M=max(R,G,B) and m=min(R,G,B). Inaddition, the lightness (L) and saturation (S) are described by thefollowing equations:

L=½(M+m)

S=(M−m)/(1−|2L−1|).

For the calibration curve, human serum is used and augmented usingCholesterol Lipid Concentrate in order to cover the whole range ofphysiological cholesterol levels. At each cholesterol concentration inthe relevant physiological range (140 mg/dl to 400 mg/dl) the test stripwas first analyzed using the CardioChek portable Blood Test System andthen imaged using the smartphone system. FIG. 15( a) shows thevariations in lightness and saturation for images acquired using thesmartphone system. The cholesterol reading is first obtained using theCardioChek portable Blood Test System. The hue values showed very littlevariation across the whole range of cholesterol values. However, huevalues can be used to indicate if a test is successful or if it failsdue to image acquisition or test strip issues. The relationship betweenconcentration and saturation can be described by a second orderpolynomial,

[Chol]=0.08S2−4.56S+196.84.

As can be seen in FIG. 15( b), this allows almost perfect matching witha maximum error of 1.8%.

The software app used in this example is illustrated in FIG. 2. When theuser presses “analyze” on the app, an image of the colorimetric colorchanges is acquired through the iPhone camera. The app then executesseveral processing steps before the cholesterol value is displayed onthe smartphone screen. First, a 100 px by 100 px calibration area isselected at the bottom right corner of the image. The average RGB valueis computed and converted to HSL. This average HSL value is thencompared to a reference value and a background shift is computed. Thewhole image is then is subjected to this background shift. After thebackground shift, a 100 px by 100 px area in the middle of the detectioncircle is selected and the same computation as before is done to obtainthe average HSL value of the test area. The algorithm then verifies ifthe test is valid by comparing the average hue value to the typicalvalue of the cholesterol test, which is constant across physiologicalcholesterol values (H˜180) both for serum samples and blood samplesduring test trials. In order to decrease fluctuations due to lightingconditions, the strip is imaged three times and the average hue valueover those three images is taken. If the hue value falls within therange of expected hue values, then the cholesterol level is calculatedusing the calibration curve previously obtained. The ability ofidentifying bad samples is a major advantage over other specializedhand-held devices that use reflectance photometry to quantifycolorimetric reaction.

A critical issue to consider for point-of-care testing is the accuracyof the measurement. Once the user applies a drop of blood on the stripit takes some time for the colorimetric change to occur on the otherside of the strip since the blood goes through several separation stepsand chemical reactions and the colorimetric change occurs gradually ascan be seen at the bottom of FIG. 14. If the strip is imaged before thereaction has terminated then we will get a misleadingly low value forthe blood cholesterol level. In order to determine the approximate timerequired for the reaction to occur we have monitored the color changefor a serum sample with an actual concentration of 178 mg/dl. As can beseen in FIG. 14( a), it takes about 60 s for the colorimetric change tostabilize. The variation in predicted cholesterol levels are containedwithin less than 3.9% of the actual value after that; however, the valueshifts up as time elapses. It is therefore important to be consistent bybuilding in the algorithm a time frame for imaging the test strip. Inaddition, averaging several acquired images during that time frame canhelp further improve the accuracy.

Embodiments of the invention are related to a smartphone apparatus, asmartphone accessory, a method for obtaining a point-of-collection,selected qualitative and/or quantitative indicia of an analyte on a testplatform, and a portable, modular, point-of-collection,colorimetric-based diagnostic system including the aforementionedsmartphone, smartphone accessory, and an executable application residentin the smartphone enabling/performing the aforementioned method, asfurther described herein below. Exemplary aspects include asmartphone-based platform for qualitative and/or quantitative readout oflateral flow immunochromatographic assays, and associated methods andapplications.

The smartphone platform includes an accessory 1602 as shown in FIG.16(A, B, C) that attaches to the smartphone camera (not shown), andconsumable lateral flow tests (strips) 1604 (not part of the inventionper se) that are inserted into the accessory. A smartphone application(“app”) 1707 (FIG. 17(B)) operates the smartphone camera, interprets theresults automatically, displays the results to the user, and archivesthem to enable long term tracking.

In the embodiment described herein above for colorimetric analysis asapplied, e.g., to cholesterol monitoring, the color change of the teststrip was accurately obtained without providing a focused image of theregion of interest. For the instant embodied aspect for the readout oflateral flow assays, it is advantageous to obtain magnified and focusedimages of the test region as both the color intensity and the shape(line shape, width etc.) of the signal lines developed are of interest.The instant aspect thus includes a lens 1612 to focus and magnify thetest strip region of interest, and a LED 1614 to ensure consistentillumination for imaging, as shown in FIG. 16(C). The battery 1617 (FIG.16(B)) powers the LED and the switch 1618 enhances the efficiency of theLED operation by allowing the user to turn on the LED only duringoperation. The test strip holder accepts the lateral flow test stripsand includes a cap 1620(??) to enclose the sample collection pad afterthe strip is exposed to the sample.

Example

The inventors have developed a first generation smartphone prototype forreading lateral flow test strips and accurately determining the numberof colorimetric lines that develop, thereby being able to distinguishbetween a positive and a negative result. Here the preliminaryperformance of the smartphone technology was demonstrated using thelateral flow assays for human chorionic gonadotropin (hCG), widely knownas pregnancy tests.

To conduct the preliminary test for hCG, the user first attaches theaccessory 1602 to the smartphone 1701. Their alignment is such that thebuilt-in lenses of the smartphone and the accessory lens are aligned forenhanced imaging. Upon dipping the test strip in a sample and cappingthe collection end to prevent contamination, the user inserts the teststrip into the accessory as shown in FIG. 17(A). A mechanical stoppermechanism (not shown) is incorporated into the design of the test stripholder and the accessory such that the region of interest on the teststrip is positioned consistently across different test strip insertionprocesses. Next, the user opens the smartphone ‘app’ 1707 and selectsthe desired test, as suggested in FIG. 17(B). The “analyze” button 1711of the final screen 1712 initiates a count-down (e.g., 3 minutes for hCGtests), after which a magnified and focused image of the test strip iscaptured and processed by the ‘app’ before the results are displayed tothe user.

After an image is captured by the smartphone app, it is then filteredand processed to optimize the limit of detection and improve accuracyover normal visual inspection. The grayscale intensity of the raw imagewas found to be not sufficient to accurately distinguish a shallowcontrol line from the background. To ensure accurate detection of thetest line, a series of image processing steps are performed to improvethe signal to noise ratio and allow for automatic line detection.

A schematic overview of the image processing algorithm is shown in FIG.18(A). First, a 3×3 Gaussian filter 1802 is applied to the raw image tosmooth out some of the noise. The image is then converted to the HueSaturation Luminosity (HSL) color space 1804 so that the hue channel canbe used as a single-channel measurement that distinguishes thebackground from the colorimetric lines. The hue of the colored controland test lines are lower than the hue of the background, so that thepresence of a line can be detected by finding a local minimum in the huedata. After the color space conversion, the 2D image is reduced to a 1Darray 1805/1806 by replacing each row in the 2D image with the medianhue value along that row. The median filtering reduces the noise, andthe lower dimensionality reduces the process of peak detection to a 1Ddigital signal processing problem.

The local minima 1809 corresponding to the test 1807 and control 1808lines are now located by stepping through the 1D array and storing allpoints which are at least 10 hue values below the last inflection pointon both sides. The number of detected minima yields binary test results:for negative tests, only one line should be detected (FIG. 18(C)), andfor positive tests both the control and test lines should be detected(FIG. 18(B)). Although the test strip is designed for qualitative binaryresults, the relative shape and magnitude of the two detected peaks canalso be compared to give quantitative data about the analyteconcentration, which would be inaccessible without the image analysissoftware.

One of the key advantages of the image processing analysis over visualinspection is that the testing protocol can be controlled carefully tominimize user error. Because the colorimetric reaction is only validover a certain time interval, the test strip protocol requires that theresults be discarded if taken before or after an optimal three minutewindow. Using the device presented, however, every measurement is takenat the same controlled time after the test strip is inserted, removingthe possibility of accidentally falling outside the allowed window.

The device can also ensure quality measurements by checking for teststrip errors and misalignment during the analysis. For a test to bevalid, the control line must be visible; if no peak is detectable in theappropriate region on the image, either the test strip did not developproperly, or the strip is misaligned in the device. In either case, thesoftware app will reject this measurement and give a warning that a newtest strip should be used. This reduces the possibility of a falsenegative result. Similarly, the relative magnitude of the test andcontrol lines (T/C ratio) is an indication of the concentration of theanalyte. Because the T/C ratio can be calculated during the analysis,positive test results that result in too low a T/C to be statisticallysignificant can be repeated to minimize the possibility of falsepositive results.

The embodied device uses a focusing lens 1612 to magnify the image ofthe strip and an LED 1614 for uniform illumination. It would also bepossible to eliminate the externally powered LED and instead use analternate light source such as the built-in smartphone camera flash (notshown). This would lower the complexity of the device but also remove adegree of control over the lighting conditions across smartphone modelsand platforms. It would also be possible to modify (or remove) thefocusing lens by changing the optical path length of the device, whichwould again lower the complexity but increase the size of the device tomake it less portable.

In principle, the detection mechanism disclosed herein would beapplicable to any colorimetric lateral flow assay with distinct test andcontrol lines that can be observed. While the use of a dedicated devicewith image processing software is not necessary in all cases, there area certain class of applications that require high accuracy and highsecurity where such an approach is highly advantageous. The devicepresented has a number of checks in place to safeguard against errors inboth the user protocol and in the test strip manufacturing itself, andthe results of the test are stored instantaneously and cannot be alteredby the user. In the context of law enforcement or work place drugscreening, for instance, this added security protects against tamperingwith the data, as well as costly false positive results. The device alsohas several key advantages for medical diagnostics due to the increasedaccuracy at making qualitative (binary) measurements, as well as theenablement of quantification. Data security and confidentiality are alsomajor concerns in a hospital or clinical environment, which is anotherbenefit of using a digital reader that can be easily connected to aHIPAA-compliant database for secure long-term storage.

All references, including publications, patent applications, andpatents, cited herein are hereby incorporated by reference to the sameextent as if each reference were individually and specifically indicatedto be incorporated by reference and were set forth in its entiretyherein.

The use of the terms “a” and “an” and “the” and similar referents in thecontext of describing the invention (especially in the context of thefollowing claims) are to be construed to cover both the singular and theplural, unless otherwise indicated herein or clearly contradicted bycontext. The terms “comprising,” “having,” “including,” and “containing”are to be construed as open-ended terms (i.e., meaning “including, butnot limited to,”) unless otherwise noted. The term “connected” is to beconstrued as partly or wholly contained within, attached to, or joinedtogether, even if there is something intervening.

The recitation of ranges of values herein are merely intended to serveas a shorthand method of referring individually to each separate valuefalling within the range, unless otherwise indicated herein, and eachseparate value is incorporated into the specification as if it wereindividually recited herein.

All methods described herein can be performed in any suitable orderunless otherwise indicated herein or otherwise clearly contradicted bycontext. The use of any and all examples, or exemplary language (e.g.,“such as”) provided herein, is intended merely to better illuminateembodiments of the invention and does not impose a limitation on thescope of the invention unless otherwise claimed.

No language in the specification should be construed as indicating anynon-claimed element as essential to the practice of the invention.

It will be apparent to those skilled in the art that variousmodifications and variations can be made to the present inventionwithout departing from the spirit and scope of the invention. There isno intention to limit the invention to the specific form or formsdisclosed, but on the contrary, the intention is to cover allmodifications, alternative constructions, and equivalents falling withinthe spirit and scope of the invention, as defined in the appendedclaims. Thus, it is intended that the present invention cover themodifications and variations of this invention provided they come withinthe scope of the appended claims and their equivalents.

TABLE 1 Quantification Application(s) Target Required Fluid BasicElectrolytes Basic Metabolic Panel Sodium (Na) Yes Blood (ManyDiagnosis) Basic Metabolic Panel Potassium (K) Yes Blood (ManyDiagnosis) Basic Metabolic Panel Chloride (Cl) Yes Blood (ManyDiagnosis) Basic Metabolic Panel Bicarbonate (Dissolved CO₂) Yes Blood(Many Diagnosis) Kidney Function Kidney Function Urea (Blood UreaNitrogen, Yes Blood Tests BUN) Kidney Function Creatinine Yes BloodProtein Tests Kidney and Liver Serum Calcium Yes Blood (useful forKidney Function and Liver Kidney and Liver Serum Total Protein (TP) YesBlood Problems) Function Kidney and Liver Human Serum Albumin Yes BloodFunction Liver Function Liver Function Bilirubin Yes Blood Tests LiverFunction Alkaline phosphatase (ALP) Yes Blood Liver Function Aspartateamino transferase Yes Blood (AST or SGOT) Liver Function Alanine aminotransferase Yes Blood (ALT or SGPT) Cholesterol Test Atherosclerosis,Total Cholesterol Yes Blood Panels Coronary Disease, High CholesterolAtherosclerosis, HDL Yes Blood Coronary Disease, High CholesterolAtherosclerosis, LDL Yes Blood Coronary Disease, High CholesterolAtherosclerosis, Triglycerides Yes Blood Coronary Disease, HighCholesterol General Tests and Diabetes, Basic Glucose Yes BloodMiscellaneous Metabolic Panel Calcium (Ca) Yes Blood (Many Diagnosis)Osteoporosis, Basic C Reactive Protein Yes Blood Metabolic PanelHemoglobin A1C Yes Blood (Many Diagnosis) Inflammation Chloride YesSweat Diabetes, Long term pH Yes Sweat high glucose Cystic Fibrosisandrogens (DHEA, Yes Saliva Dehydration testosterone) Hypogonadismallergen-specific IgA No Saliva Allergies Diagnosis of PCOS,Testosterone Yes Saliva hormonal imbalance Renal Injury in HIV+β-2-microglobulin (β2MG) Yes Urine Patients TNF-like weak inducer of YesUrine apoptosis Lupus HBV surface antigen Yes Saliva Hepatitis anti-HCVYes Saliva Hepatitis melatonin Yes Saliva Pineal Physiology inuroporphyrin, Yes Urine newborns coproporphyrin Prorphyria sweatproteins¹ Yes Sweat Schizophrenia Fatty acid ethyl esters Yes SweatIntoxication Liver Disease parasite Entamoeba Yes Saliva histolyticaTissue Damage lactate, chloride, urea, and Yes Sweat urate Heart AttackPanel Myocardial Infarction Troponin Yes Blood (heart attack) MyocardialInfarction Myoglobin Yes Blood (heart attack) Myocardial InfarctionCK-MB Yes Blood (heart attack) Myocardial Infarction C Reactive ProteinYes Saliva (heart attack) Blood Clotting Prothrombin Time andProthrombin Time and INR Yes Blood Tests INR Clotting Problems,Fibrinogen Yes Blood Cardiovascular Disease, Inflammation Cancer TestsProstate Cancer sarcosine Yes Urine Prostate Cancer prostate cancerantigen 3 Yes Urine (PCA3) Prostate Cancer Prostate-Specific Antigen YesBlood (PSA) Ovarian Cancer Estrogen Yes Saliva Bladder Cancer NMP22 YesUrine Breast Cancer Lipid peroxides Yes Saliva Breast Cancer tumorsuppressor protein p53 Yes Saliva Oral Cancer transferrin Yes SalivaOral Cancer Cyclin D1/Maspin Yes Saliva Pancreatic Cancer mRNAbiomarkers Yes Saliva Vitamin Tests Bone Health, vitamin D Yes BloodOsteoporosis, Cancer, Depression Pregnancy, Neural Folate Yes Blood TubeDefects vitamin C Yes Urine vitamin C levels Many other vitamin vitaminB12, vitamin A, etc. Yes Blood tests can be performed colorimetricallyHormone and Cardiovascular Health, DHEA Yes Blood, Steroid Tests Saliva(Including Thyroid Reproductive Health Thyroid Stimulating Yes BloodFunction Tests) elevated in Hormone (TSH) hypothyroidism & decreased inhyperthyroidism disorders associated with testosterone abnormalitiesOvarian Activity and Testosterone (Free) Yes Blood health A number ofother tests Estradiol Yes Blood also exist Infectious Disease SexuallyTransmitted Infection AIDs, viral Infection Chlamydia (anti-LPS) No HIVToxoplasma gondii IgM and gG antibodies No Saliva, infection BloodHelicobacter pylori IgM and gG antibodies Yes Saliva Infection Manyother infections IgM and gG antibodies Yes Saliva Other electrolytesGeneral Testing pH Yes Blood and minerals General Testing Copper YesBlood General Testing Iron Yes Blood General Testing Phosphate Yes BloodGeneral Testing Ammonia Yes Blood General Testing Lithium Yes BloodGeneral Testing Magnesium Yes Blood Substance Levels Check DosageAcetaminophen(Tylenol) Yes Blood (i.e. Drugs) Cannabis use CannabinoidsNo Blood, Drug use (one test for Ecstasy, Heroin, Cocaine, Urinemultiple targets) and others Yes Blood, Drug use 6-monoacetylmorphineUrine Drug use amphetamine No Saliva Drug use methamphetamine No SalivaDrug use N-desmethyldiazepam No Saliva Alcohol Use ethanol No SalivaDrug use opiates, methadone, Yes Urine morphine, benzodiazepinesPregnancy Related Ovulation Testing hCG Yes Urine Targets OvulationTesting luteinizing hormone (LH), Yes Urine E3G Ovulation Testingluteinizing hormone (LH) Yes Saliva Diabetes Diabetes, Basic Glucose YesBlood Measurements Metabolic Panel (Many Diagnosis) Diabeteschromogranin A Yes Saliva Urine Test Strips Carbohydrate GlucoseImproves Test Urine (Siemens) Disorders like Diabetes Bilirubin ImprovesTest Urine Liver Disease and Ketone (Acetoacetic Acid) Improves TestUrine Jaundice Carbohydrate Specific Gravity Improves Test UrineDisorders like Diabetes Blood Improves Test Urine Measure of Kidney pHImproves Test Urine Function for General Disease Most often used toProtein Improves Test Urine notice trauma to kidneys Multiple uses, lungand Urobilinogen Improves Test Urine kidney function, therapeutic usesShould be low, higher can indicate nephropathy of multiple locationsLiver Function Urinary Tract Infection Nitrite Improves Test UrineUrinary Tract Infection Leukocytes Improves Test Urine DentalApplications Periodontitis pH Yes Saliva Periodontitis peroxidase YesSaliva Periodontitis hydroxyproline Yes Saliva Periodontitis calcium YesSaliva Pregnancy gingivitis estrogens Yes Saliva risk Dermatology atopicskin conditions free amino acid composition Yes Sweat ApplicationsDepression Stress Level Cortisol Yes Urine Stress Level Cortisol YesSaliva Major depressive pro-inflammatory cytokines Yes Sweat disorder(MDD) and neuropeptides Major depressive adiponectin, leptin, ACTH YesSweat disorder (MDD) and cortisol secretion Stress Related neuropeptideY Yes Sweat Other Iron Panel Tests

We claim:
 1. A method for obtaining a point-of-collection, selectedquantitative indicia of an analyte on a test platform, comprising:providing a modular, colorimetric reactive test platform having a testregion and a calibration region; providing an analyte to be tested onthe test region of the modular, colorimetric test platform, wherein thetest region is adapted to enable a colorimetric reaction to the analyte;obtaining a color image of the test region containing the analyte andthe calibration region; selecting an array of pixels in each of thecolor images of the test region containing the analyte and thecalibration region; determining a median RGBA color value for each ofthe arrays of pixels; converting the median RGBA color value for each ofthe arrays of pixels to a respective Hue-Saturation-Luminosity (HSL orHSV) test color space value and a HSL or HSV calibration color spacevalue; providing a calibration indicia that relates a selectedquantitative indicia of the analyte to a characteristic of the HSL orHSV calibration color space value; and associating a median HSL or HSVtest color space value with the HSL or HSV calibration color space valueto determine the selected quantitative indicia of the analyte.
 2. Themethod of claim 1, wherein the colorimetric reactive test platform issensitive to at least one of a chemical colorimetric reaction, anenzymatic colorimetric reaction, and a gold nanoparticle colorimetricreaction.
 3. The method of claim 1, wherein the modular, colorimetrictest platform is a disposable test strip.
 4. The method of claim 1,wherein the indicia of the analyte is one of pH, cholesterol, andvitamin D.
 5. The method of claim 1, wherein the calibration regionmaintains a constant color in the presence of a varying amount of theselected indicia of the analyte.
 6. The method of claim 5, wherein thecalibration region includes a plurality of calibration regions each ofwhich has a different calibration color.
 7. The method of claim 1,wherein the calibration indicia is a calibration curve that relates theselected quantitative indicia of the analyte to a hue value of the HSLor HSV calibration color space value.
 8. The method of claim 1,comprising obtaining the color image of the test region containing theanalyte and the calibration region using a smartphone including a lightsource and an image detector.
 9. The method of claim 8, furthercomprising displaying the determined selected quantitative indicia ofthe analyte on the smartphone.
 10. The method of claim 8, furthercomprising providing a smartphone accessory that can be removeablycoupled to the smartphone, wherein the smartphone accessory is adaptedto receive the modular, colorimetric test platform, further wherein atleast one of the modular, colorimetric test platform and the smartphoneaccessory includes a light diffuser and/or a light-diffusing pathway soas to ensure a uniform and repeatable illumination of at least a desiredregion of the modular, colorimetric test platform, further wherein thesmartphone accessory is substantially light-tight when the test platformis disposed therein, so as to enable consistent internal illuminationconditions independently of any external conditions.
 11. The method ofclaim 10, wherein the light source is one of an internal smartphoneflash source and an external LED source.
 12. The method of claim 8,further comprising time stamping the determined selected quantitativeindicia of the analyte and storing the determined value for futureaccess.
 13. The method of claim 8, further comprising location stampingthe determined selected quantitative indicia of the analyte and storingthe determined value for future access.
 14. The method of claim 12 orclaim 13, comprising storing the time and/or location data in at leastone of a readable file in the smartphone, an external readable file, andin a Cloud file.
 15. The method of claim 12 or claim 13, furthercomprising determining a temporal and/or a location trend of a pluralityof the determined selected quantitative indicia of the analyte.
 16. Themethod of claim 8, further comprising correlating the determinedselected quantitative indicia of the analyte to a related selectedmetric and displaying a value of the related selected metric on thesmartphone.
 17. The method of claim 1, wherein the analyte is one ofsweat, saliva, blood, tears, urine, and other bodily fluids.
 18. Themethod of claim 10, wherein obtaining a color image of the test regioncontaining the analyte and the calibration region further comprisesilluminating a rear surface of the test strip that is facing the lightsource with diffused light from the light source.
 19. The method ofclaim 1, wherein the step of obtaining a color image of the test regioncontaining the analyte and the calibration region comprises illuminatinga rear surface of the modular, colorimetric test platform.
 20. Themethod of claim 8, comprising using a brand-independent oroperating-system-independent smartphone.
 21. A smartphone accessory foruse in a smartphone-based point-of-collection, colorimetric-based,quantitative measuring system, comprising: a housing that can beremoveably attached to the smartphone in a manner that at leastoptically couples the smartphone accessory to a resident smartphonecamera, wherein the housing is opaque such that the smartphone accessoryis substantially externally light-tight when a test strip is disposedtherein, further wherein the housing includes at least one of adesigned-in optical pathway and a light diffuser in the housing forproviding diffuse illumination of a surface of the test strip disposedtherein from an internal light source resident in the housing or anexternal light source resident in the smartphone to which the smartphoneaccessory can be attached.
 22. The smartphone accessory of claim 21,wherein the designed-in optical pathway in the housing comprises a wallthat creates an indirect optical path between the external light sourceresident in the smartphone to which the smartphone accessory can beattached and a resident smartphone camera in the smartphone to which thesmartphone accessory can be attached.
 23. The smartphone accessory ofclaim 21, wherein the light diffuser is disposed intermediate theexternal light source resident in the smartphone to which the smartphoneaccessory can be attached and a non-colorimetric-reactive region of thetest strip when the test strip is disposed in the housing.
 24. Thesmartphone accessory of claim 21, wherein the at least one of thedesigned-in optical pathway and the light diffuser is disposed in amanner to provide diffuse illumination of a rear surface of the teststrip.
 25. The smartphone accessory of claim 21, further comprising: alight source disposed in the housing; a light diffuser disposedintermediate the light source and a resident smartphone camera in thesmartphone to which the smartphone accessory can be attached, in amanner to provide diffuse illumination of a rear surface of a test stripwhen the test strip is disposed in the housing; and a power source forthe light source, disposed in the housing.
 26. A portable, modular,point-of-collection, colorimetric-based diagnostic system, comprising: asmartphone including an image detector; the smartphone accessory ofclaim 21; and an executable application resident in the smartphone that,in operation, performs the following steps: acquires an image of atleast a portion of the test strip; stores the image as an RGBA bytearray; splits the image into a test image and a calibration image; forthe calibration image: extracts a calibration array of pixels;determines a median RGBA color value for the calibration array ofpixels; converts the median RGBA color value for the calibration arrayof pixels to a calibration Hue-Saturation-Luminosity (HSL or HSV) colorspace value; adjusts the calibration HSL or HSV color space value to acalibration indicia of a selected quantitative indicia of an analyte tobe measured; and for the test image: extracts a test array of pixels;determines a median RGBA color value for the test array of pixels;associates the median RGBA color value for the test array of pixels tothe calibration HSL or HSV color space value; and determines aquantitative value of the selected indicia of the analyte to bemeasured.
 27. The system of claim 26, wherein the light source is aninternal flash source of the smartphone.
 28. The system of claim 26,wherein the light source is an LED disposed in the smartphone accessory,further comprising a battery in the smartphone accessory to power theLED.
 29. The system of claim 26, wherein the system is smartphoneplatform-independent.
 30. The system of claim 26, wherein the smartphoneaccessory is an unpowered component.
 31. The system of claim 26, furthercomprising a colorimetric reactive test strip that is removeablydisposable in the smartphone accessory.
 32. The system of claim 31,wherein the colorimetric reactive test strip includes a colorimetricreactive test region and a non-colorimetric reactive calibration region.33. The system of claim 30, wherein the colorimetric reactive testregion is at least one of chemically colorimetric reactive,enzymatically colorimetric reaction, and gold nanoparticlecolorimetrically reactive.
 34. The system of claim 31, wherein thecolorimetric reactive test strip includes a light diffuser.
 35. Thesystem of claim 34, wherein the light diffuser is one of a PDMS membraneand an adhesive tape disposed on at least a portion of a surface of thetest strip.
 36. The system of claim 32, wherein the non-colorimetricreactive calibration region comprises a glossy material.
 37. The systemof claim 34, wherein the light diffuser is disposed on the at least aportion of a surface of the test strip is such a manner to providediffuse illumination to a rear surface of the test strip.
 38. The systemof claim 26, comprising a brand-independent oroperating-system-independent smartphone.
 39. A method for obtaining apoint-of-collection, selected qualitative and/or quantitative indicia ofan analyte on a test platform, comprising: providing a modular assaytest platform (e.g., test strip) having at least one test region and acontrol region; providing an analyte to be tested on the at least onetest region; obtaining an image of the at least one test regioncontaining the analyte and the control region; selecting an array ofpixels in the image of the at least one test region containing theanalyte and the control region; determining a RGBA color value for eachof the arrays of pixels; extracting a test image region for analysis;converting the RGBA array to an alternate color space as determined bythe specific test including but not limited to HSL, HSV, or greyscale;determining one of a median, mean, maximum, minimum, or otherstatistical measure of the color or intensity value for various regionsof the test platform that may or may not contain test or control areasand creating at least a 1D array containing these values; if necessary,determining a low-frequency variation in color or intensity value overthe array and, if necessary, performing illumination correction andbackground subtraction; detecting a peak or valley in the adjusted arraycorresponding to the test and control regions to be measured;determining a depth, width, height (for example, based on intensity orcolor maxima/minima), and/or area (for example, based on integratedcolor or intensity) of these peaks or valleys which correspond todetection or control regions of the test platform; and determining aqualitative presence of the selected indicia of the analyte by thenumber of peaks or valleys present, and/or a quantitative value of theselected indicia of the analyte by quantitative comparison of two ormore peaks or valleys.
 40. The method of claim 39, wherein the assaytest platform is sensitive to at least one of a chemical colorimetricreaction, an enzymatic colorimetric reaction, and a gold nanoparticlecolorimetric reaction, including a lateral flow type immunoassay. 41.The method of claim 39, wherein the assay test platform is a disposablelateral flow immunochromatographic test strip.
 42. The method of claim39, comprising obtaining the image of the at least one test regioncontaining the analyte and the control region using a smartphoneincluding a light source and an image detector.
 43. The method of claim42, further comprising displaying the determined selected indicia of theanalyte on the smartphone.
 44. The method of claim 42, furthercomprising providing a smartphone accessory that includes: a housingthat can be removeably attached to the smartphone in a manner that atleast optically couples the smartphone accessory to a residentsmartphone camera; a lens that allows for adjustment of the focal lengthof the smartphone camera to enable imaging of the test platform in acompact device, wherein the housing is opaque such that the smartphoneaccessory is substantially externally light-tight when the test platformis disposed therein, further wherein the housing includes at least oneof a designed-in optical pathway and a light diffuser in the housing forproviding diffuse illumination of a surface of the test platformdisposed therein from an internal light source resident in the housingor an external light source resident in the smartphone to which thesmartphone accessory can be attached.
 45. The method of claim 44,wherein the light source is one of an internal smartphone flash sourceand an external LED source.
 46. The method of claim 42, furthercomprising at least one of time stamping and location stamping thedetermined selected quantitative indicia of the analyte and storing thedetermined value for future access.
 47. The method of claim 46,comprising storing the time and/or location data in at least one of areadable file in the smartphone, an external readable file, and in aCloud file.
 48. The method of claim 46, further comprising determining atemporal and/or a location trend of a plurality of the determinedselected quantitative indicia of the analyte.
 49. The method of claim42, further comprising correlating the determined selected quantitativeindicia of the analyte to a related selected metric and displaying avalue of the related selected metric on the smartphone.
 50. The methodof claim 39, wherein the analyte is one of sweat, saliva, blood, tears,urine, and other bodily fluids.
 51. The method of claim 44, whereinobtaining the image of the test region or regions containing the analyteand the control region or regions further comprises illuminating asurface of the test platform that is illuminated by the light sourcewith diffused light from the light source.
 52. The method of claim 39,wherein the step of obtaining the image of the test region or regionscontaining the analyte and the control region or regions comprisesilluminating a surface of the modular, colorimetric test platform. 53.The method of claim 42, comprising using a brand-independent oroperating-system-independent smartphone.
 54. The method of claim 39,wherein obtaining an image of the at least one test region comprisesobtaining multiple images denoting changes in the indicia over time,which can be used to provide an improved estimate of the initialconcentration of the analyte.
 55. The method of claim 39, whereinobtaining an image of the at least one test region comprises obtainingmultiple images denoting changes in the indicia over time, which can beused to serve as a method for detecting an error with the test.
 56. Asmartphone accessory for use in a smartphone-based point-of-collection,system, comprising: a housing that can be removeably attached to thesmartphone in a manner that at least optically couples the smartphoneaccessory to a resident smartphone camera; a lens that allows foradjustment of the focal length of the smartphone camera to enableimaging of the test strip in a compact device, wherein the housing isopaque such that the smartphone accessory is substantially externallylight-tight when a test strip is disposed therein, further wherein thehousing includes at least one of a designed-in optical pathway and alight diffuser in the housing for providing diffuse illumination of asurface of the test strip disposed therein from an internal light sourceresident in the housing or an external light source resident in thesmartphone to which the smartphone accessory can be attached.
 57. Thesmartphone accessory of claim 56, wherein the designed-in opticalpathway in the housing comprises a wall that creates an indirect opticalpath between the external light source resident in the smartphone towhich the smartphone accessory can be attached and a resident smartphonecamera in the smartphone to which the smartphone accessory can beattached.
 58. The smartphone accessory of claim 56, wherein the lightdiffuser is disposed intermediate the external light source resident inthe smartphone to which the smartphone accessory can be attached and anon-colorimetric-reactive region of the test strip when the test stripis disposed in the housing.
 59. The smartphone accessory of claim 56,wherein the at least one of the designed-in optical pathway and thelight diffuser is disposed in a manner to provide diffuse illuminationof a surface of the test strip.
 60. The smartphone accessory of claim56, further comprising: a light source disposed in the housing; a lightdiffuser disposed intermediate the light source and a residentsmartphone camera in the smartphone to which the smartphone accessorycan be attached, in a manner to provide diffuse illumination of asurface of a test strip when the test strip is disposed in the housing;and a power source for the light source, disposed in the housing.
 61. Aportable, modular, point-of-collection, colorimetric-based diagnosticsystem, comprising: a smartphone including an image detector; thesmartphone accessory of claim 56; and an executable application residentin the smartphone that, in operation, performs the following steps:obtaining an image of the at least one test region containing theanalyte and the control region; selecting an array of pixels in theimage of the at least one test region containing the analyte and thecontrol region; determining a RGBA color value for each of the arrays ofpixels; extracting a test image region for analysis; converting the RGBAarray to an alternate color space as determined by the specific testincluding but not limited to HSL, HSV, or greyscale; determining amedian color or intensity value for the pixels in each row, and creatingat least a 1D array containing these values; determining a low-frequencyvariation in color value over the array and performing illuminationcorrection and background subtraction; detecting a peaks or valley inthe adjusted array corresponding to the test and control lines to bemeasured; determining a depth or height (intensity maxima/minima) and/orarea (integrated intensity) of these peaks which correspond to detectionlines of the test strip; and determining a qualitative presence of theselected indicia of the analyte by the number of peaks present, and/or aquantitative value of the selected indicia of the analyte byquantitative comparison of two or more peaks.
 62. The system of claim61, wherein the light source is an internal flash source of thesmartphone.
 63. The system of claim 61, wherein the light source is anLED disposed in the smartphone accessory, further comprising a batteryin the smartphone accessory to power the LED.
 64. The system of claim61, wherein the system is smartphone platform-independent.
 65. Thesystem of claim 61, wherein the smartphone accessory is an unpoweredcomponent.
 66. The system of claim 61, further comprising a colorimetricreactive test strip that is removeably disposable in the smartphoneaccessory.
 67. The system of claim 66, wherein the colorimetric reactivetest strip includes at least one test region and a control region. 68.The system of claim 66, wherein the colorimetric reactive test region isat least one of chemically colorimetric reactive, enzymaticallycolorimetric reaction, and gold nanoparticle colorimetrically reactive,including a lateral flow type immunoassay.
 69. The system of claim 61,wherein the light diffuser is disposed on the at least a portion of asurface of the test strip is such a manner to provide diffuseillumination to a surface of the test strip.